Data Scientist jobs in Israel

Description We are hiring a Principal Data Scientist for the Data Science group, reporting directly to the VP Engineering. This is a senior individual-contributor leadership role: you own the technical direction and architecture of what the group ships - real-time inference at scale, automated red-teaming of GenAI systems, and the Databricks/Spark data platform underneath - and you lead the hardest projects end to end, hands on in the code. What you'll own A large Python, Rust, and PySpark monorepo, dozens of production services and shared libraries, across three connected domains: Content-moderation inference at scale Real-time, multi-tenant detection across text, image, video, and audio - hate speech, CSAM, nudity, child grooming, extremism, PII, prompt injection, age estimation, and more - served through our in-house ActiveServe framework over NVIDIA Triton and a Rust detection service, on latency-sensitive, SLA-bound, customer-facing traffic with per-customer custom models. GenAI safety and red-teaming Automated red-teaming that attacks customers' LLM applications with a research-driven attack taxonomy and measures attack-success rate, alongside the defensive side - LLM-as-judge escalation to cut false positives, and the tooling that authors and refines moderation policies - built on a multi-provider LLM foundation (Bedrock, Anthropic, OpenAI, Gemini, xAI Grok). Data platform and MLOps An end-to-end lakehouse and MLOps stack on Databricks - bronze/silver/gold ingestion, PySpark pipelines, and model training, versioning, and promotion through MLflow / Unity Catalog into Triton serving - with the performance-critical hot paths engineered in Rust (PyO3/maturin) for sub-millisecond, high-QPS matching and detection. What you'll do • Own the GenAI safety roadmap - decide what we build with LLMs and what we build around them: guardrails and LLM-as-judge adjudication, prompt-injection and jailbreak detection, policy authoring, and the automated red-teaming that measures attack-success rate against customers' applications. Choose which model families and providers we use, fine-tune, or retire, and what each has to prove before it reaches customer traffic. • Own how we evaluate GenAI systems - benchmark and dataset design over real production traffic, LLM-jury labeling protocols, multilingual, multi-turn, and multimodal coverage, calibration and threshold selection, and the error analysis that turns a metric into a fix. Run the evaluations that separate a real shift in what these models can do from a launch post, and keep quality honest in production as traffic, prompts, and attacks drift. • Lead the hardest GenAI work end to end, and grow the craft - take the ambiguous, high-stakes projects from framing through prototype, offline evaluation, shadow traffic, and rollout; mentor data scientists and ML engineers through design, experiment, and model review; and translate model behavior into what Product and customers care about: accuracy, latency, cost, and enterprise readiness. Requirements What we're looking for • ML technical leadership - a proven tech lead, senior data scientist, or ML engineer who has taken multi-person, multi-quarter ML initiatives from framing to production without formal authority, with strong Python and the written communication to make the case in a design or an evaluation. • Deep understanding of LLM technology - how these models are trained, adapted, and served, what prompting, fine-tuning, RAG, and agentic patterns each buy you, where they fail, and how to measure quality, latency, and cost. • AI-augmented engineering - deep, daily fluency with an AI coding assistant (Claude Code, Cursor, or Codex), with the judgment to raise the whole team's leverage and set how these tools are used well. About Alice Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

About Teads Teads is a leading omnichannel advertising platform building the future of digital advertising where quality content, trusted publishers, ambitious brands, and human creativity can thrive. Operating at true scale - processing 18 billion ad opportunities every single day - we connect global brands with a monthly reach of over 2.2 billion unique users. At Teads, we believe your impact travels further. We are a borderless team of 1,700+ innovators across 30+ countries who favor outcome over tenure, value trusted autonomy, and use predictive AI to amplify human ingenuity rather than replace it. We move at pace, tackle genuinely complex problems, and foster a high-accountability culture that stays genuinely human. If you are looking for room to build and meaningful scope, you belong here. Learn more at www.teads.com. About the opportunity We are looking for a Senior Data Scientist to join a team of passionate engineers who build premium solutions at scale. Every day, we tackle ambiguous and stimulating challenges. We build and operate large-scale distributed machine learning systems that process 1B predictions per second during real-time auctions. What will you do? As a Senior Data Scientist, your mission will be to: • Improve existing algorithms & tools allowing to explore and analyze more and more data and provide accurate feedback on the Teads activities. • Develop new algorithms & new approaches to provide accurate predictions and drive new products by providing business insights. • Implement your algorithms and models end to end. • Collaborate with a variety of teams to develop services from design to production. • Make sure the software is in good hands by writing, running and automating tests (unit, functional, load...). • Keep up to date with the latest Machine Learning technologies to make sure we always use the best class algorithms according to the context. • Shape how billions of people discover and enjoy premium content by improving ad relevance, quality, and efficiency across Teads’ global publisher network. What will you bring to the team? • Strong communication skills, working collaboratively with the team, able to teach concepts, and communicate clearly to a wide audience of complicated topics. • Strong problem solving skills, and deducing from specific problems wider range products. • True scientist skills: fast learner, curious, sense of details, rigorous. • Experience in Statistics (i.e. statistical analysis, regression analysis, …) and Artificial Intelligence (i.e. Data Mining, Machine Learning, …). • An appetite for Data Science applied to high-volumetry, low-latency topics. • Ability to read scientific articles, to analyze critically, and to implement as appropriate. • Good programming abilities. • You are very mindful about your application architecture, performance, testing and maintainability and its overall quality. Requirements: • 5+ years of hands-on experience with coding ML based solutions in high scale systems • Relevant industry experience / publications in ad-tech and recommender system • Msc/Phd in computer science / math • Industry experience in building engineering at scale • Large-scale distributed systems, service oriented architecture. • Previous experience with all or some of the elements of our Stack (we mainly use Go, Python, Java, AWS, Jupyter notebooks). • Knowledge in data engineering. • Ability to transform raw data into actionable business insights Please submit your CV in English. Life at Teads At Teads, we don’t just offer jobs. We blend creativity, technology, and cutting-edge data to shape the future of media. As a Teadster, you’ll work alongside smart humans, collaborate with meaningful brands, and leverage advanced AI and automation to redefine how advertising works in a transparent, privacy-first world. We are builders, innovators, and future-thinkers. If you are excited by the evolution of technology and ready to embrace the future of AI-driven media, you belong here. Why Join Us? • A New Era of Media: We’ve merged two open internet category leaders, Outbrain and Teads to create a unified omnichannel platform. Together, we drive results from branding to performance across CTV, mobile, and web. • AI-Powered Innovation: We actively embrace AI and next-gen technology to solve complex industry challenges. We look for curious minds who aren't afraid to experiment, adapt, and lead the charge into the future of digital advertising. • Growth & High Performance: Our culture is dynamic, global, and built on excellence. We are committed to your success, offering the modern tools, mentorship, and development opportunities you need to thrive. • Belonging & Impact: We foster a welcoming, diverse environment where approachable, resourceful, and passionate people excel. Through our employee-led Employee Resource Groups (ERGs), you can actively drive change in areas like sustainability, women’s empowerment, charitable initiatives, and DE&I. Equal Opportunity Employer Teads is committed to diversity, equity, and inclusion at all stages of recruitment and employment. We celebrate unique perspectives and are dedicated to building a team that reflects the global communities we serve.

Description EverC, now part of G2 Risk Solutions, is a pioneer in its field. By leveraging technologies that illuminate the darkest corners of the internet and provide unparalleled visibility into the largest source of data in the world, EverC uses artificial intelligence and machine learning techniques to assess hundreds of millions of domains and effectively categorize the internet. These insights reveal hidden relationships and risks, identify an entity’s full digital fingerprint, and create new opportunities for businesses to scale efficiently and confidently. About the Role We’re looking for a hands-on Data Scientist who owns AI and LLM-powered products end to end — and cares about how they perform for real users. You will own the modeling and evaluation of our fraud and risk detection products: exploring the data, designing models and prompts, evaluating them offline, and monitoring them in production. You’ll work side by side with engineers to ship your models into large-scale, real-time systems — you drive the data science and the product outcomes, while engineering owns the platform plumbing. This is a data science role at heart. You won’t be a data engineer, but you’ll be comfortable working close to the data and the systems, and knowing your way around modern ML and data infrastructure is a strong plus. Responsibilities Data Science & Modeling • Own the design, build, and evaluation of LLM-based and classical ML models for classification, entity extraction, and risk scoring on large-scale, real-world data. • Lead prompt design and iteration — model configurations, fallback strategies, and tradeoffs between cost, latency, and quality. • Apply sound statistical judgment on adversarial, noisy, or imperfectly labeled data. • Drive the modeling decisions behind how LLMs and ML models fit into streaming, event-driven production systems. Product & Platform Partnership • Partner with engineers to ship your models into real-time streaming and large-scale batch pipelines — you own the modeling, they own the platform. • Shape internal evaluation tooling, LLM observability, and model-performance monitoring. • Define the requirements your infrastructure must meet to support rapid experimentation without hurting production reliability. Data Quality & Product Performance • Own the data-quality and product metrics that matter (precision, recall, coverage, latency, cost efficiency). • Build measurement frameworks for production systems and offline experiments. • Analyze production data to find labeling gaps, false-positive patterns, and new detection opportunities. • Drive experimentation (A/B tests, shadow deployments, offline evaluation) and back every decision with measurable business outcomes. Requirements • 5+ years applied data science / ML, including production model deployment. • Hands-on LLM prompt engineering and evaluation (not just fine-tuning theory). • Strong Python. • Experience with large-scale data processing concepts and technologies. • Strong grasp of data-intensive applications and modern data architectures. • Experience building cloud-native systems (AWS preferred). • Excellent communication and stakeholder management. • Comfortable with ambiguous, adversarial data and designing labels/heuristics where ground truth is imperfect. Preferred Qualifications A data scientist who is also fluent in the ML and data-engineering stack is a big plus: • Data & Infrastructure: Apache Spark, Kafka, Kubernetes, Docker, EMR, Airflow, Iceberg / Delta Lake, K8s • Cloud & DevOps: Infrastructure as Code (Terraform), CI/CD (GitHub Actions), monitoring & observability platforms • AI & ML: ML platforms, LLM-powered applications, vector databases

Nift is disrupting performance marketing, delivering millions of new customers to brands every month. We're hiring a hands-on Senior Applied Data Scientist to help build and scale production-grade recommendation systems that drive our core marketplace outcomes. This is not a research-only role. We're looking for someone who can take models from idea to production — running experiments, measuring business impact, and continuously improving the systems behind how Nift matches people with the right brands. You'll own the full lifecycle: exploratory analysis, data prep, modeling, testing, deployment, and post-launch measurement. The ideal candidate has worked in a real production environment, brings strong deep learning experience, and understands recommendation systems in practice — not just in theory. Success here means shipping models that move Nift's core KPIs, connecting technical work to measurable business impact, and helping the team scale with strong engineering discipline. This role is ideally based in Israel, but strong candidates in the U.S. will also be considered. What You'll Do • Own the full funnel of applied machine learning work, from idea through production • Build, improve, and deploy recommendation models that support Nift's core business goals • Tackle deep learning problems in a production setting — not just offline experimentation • Conduct exploratory data analysis, preprocessing, feature development, and modeling • Run experiments and evaluate success against business KPIs, not just model metrics • Partner with engineering and infrastructure teammates to productionize models and scale systems • Improve recommendation quality, personalization, and the business performance tied to those systems What You'll Have • 5+ years of experience in production data science environments • Strong hands-on experience taking machine learning models into production • Strong deep learning experience; proficiency with PyTorch or TensorFlow is expected • Direct experience with recommendation systems, or adjacent experience in areas like bidding or dynamic pricing • Strong Python and SQL skills • Experience working with data at meaningful scale — high-scale environments are a strong plus • The ability to measure model success through business outcomes such as revenue, conversion, churn, or similar KPIs Bonus points for: • A Master's degree, especially paired with strong production experience • A PhD paired with meaningful production-grade work (purely academic backgrounds aren't the target profile for this role) • A software engineering background — particularly for candidates who've built pipelines and production systems before moving into machine learning About Us Our mission is to reshape how people discover and try new brands by introducing them to new products and services through thoughtful "thank-you" gifts. Our customer-first approach ensures businesses acquire new customers efficiently while making customers feel valued and rewarded. We are a data-driven, cash-flow-positive company that has experienced 731% growth over the last three years. Now we're scaling to become one of the largest sources of new customer acquisition worldwide. Backed by investors who supported Fitbit, Warby Parker, and Twitter, we're poised for exponential growth and ready to demonstrate impact on a global scale.

About Bluevine Bluevine is the largest small business banking platform in the U.S., redefining how entrepreneurs manage their money. We create modern financial solutions, from checking and lending to payments and beyond, designed to help small business owners grow, thrive, and take control of their financial future. Our best-in-class technology, advanced security, and deep understanding of the small business community give our customers the confidence to focus on what they do best. Since 2013, we’ve supported more than 750,000 small businesses nationwide. Backed by leading investors like Lightspeed Venture Partners, Menlo Ventures, 83North, and Citi Ventures, our 500+ person global team shares one mission: to give small businesses the financial tools they need to succeed. We’re innovators driven by big ideas, collaboration, and real impact. Here, you’ll have the freedom to take ownership, grow your career, and make a difference for small business owners across America. Ready to shape what’s next? At Bluevine, we are building the next generation of AI-powered capabilities that support data-driven decision-making across the company. We are looking for a LeadData Scientist with hands-on experience in Generative AI, Large Language Models, and applied machine learning. What You'll Do • Research and evaluate LLMs and Generative AI techniques for business and data science use cases. • Collaborate with technical and cross-functional teams to integrate AI capabilities into existing products and workflows. • Share knowledge and support the adoption of Generative AI across the organization. • Design experiments to adapt and evaluate foundation models using internal and domain-specific data. • Build and productionize LLM-based applications, AI agents, and RAG solutions. • Develop prompting, retrieval, and evaluation strategies to improve model quality, reliability, and business impact. • Work with embeddings, vector databases, and LLM orchestration frameworks. • Apply Generative AI to use cases such as risk modeling, fraud detection, and customer analytics. • Monitor and improve the performance, cost, and reliability of AI solutions in production. What We’re Looking For • 8+ years of hands-on experience in Data Science, Machine Learning & Applied AI. Strong experience with Generative AI and Large Language Models. • Experience building LLM-based applications, AI agents, RAG solutions, or other production-oriented AI systems. • Experience with context engineering, model evaluation, fine-tuning, embeddings, or vector databases. • Strong proficiency in Python and common data science and machine learning tools. • Experience deploying and monitoring AI or machine learning solutions in production. • Strong analytical, problem-solving, communication, and collaboration skills. • Ability to work independently and translate AI capabilities into practical business solutions. Nice to Have • Experience with LLMOps, model observability, or cloud-based AI services. • Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks. • Background in financial services, risk, fraud, or customer analytics. Benefits & Perks • Excellent group health coverage • Flexible hybrid work model • Large Study Fund contribution • Salary Benchmarks and Checkpoints • Monthly meal card of TenBis or CiBus (your choice) with generous balance • Free parking for cars, scooters, and bikes • Free gym membership • Company-sponsored Mental Health Benefits • PTO, Company Holidays, and Flexible Holidays • Community-based volunteering opportunities

Who is Eleos Health? The people who deliver care in our communities and homes do some of the most important work in healthcare. But too often, theyʼre asked to spend their time navigating paperwork, administrative burden, and problems they only discover after something has already gone wrong. Eleos exists to change that. Weʼre building the system of action for community-based care - helping behavioral health, hospice, home health, and other care teams spend less time reacting to problems and more time focused on the people they serve. Powered by our Polaris AI, Eleos works alongside clinicians and their teams to understand whatʼs happening across care in real time and take action before issues become problems, reducing administrative burden, protecting revenue and compliance, and giving care teams more time and capacity to deliver great care. Our vision is a world where care teams can stay one step ahead, rather than constantly catching up. Weʼre helping shift an entire industry from reactive to proactive, and we need talented people to help us get there. Who is Eleos Health? Today, more people than ever are speaking publicly about their mental health. Whether it's ourselves, our friends and family or even public figures, taking care of your behavioral health is no longer a taboo, it's vital, and it's only human. Eleos is on a mission to help deliver the world's most effective behavioral care through data, measurement, and personalization. Or simply put, We want to give clinicians the support they need to do the important work only they can do. What is this opportunity? At Eleos, we build AI that turns behavioral health conversations into clinical documentation and actionable insights, helping care teams spend less time on administrative work and more time with the people they support. As a Senior Data Scientist, you will own the development and quality of AI capabilities that clinicians use in their daily work. You will work with real-world conversations, clinical text, and audio to build solutions for documentation, structured information extraction, and clinical insights across diverse care settings. This is a hands-on role combining experimentation, production software development, and close collaboration with engineering, product, and clinical experts. You will help define what good AI output looks like, build ways to measure it, and turn promising experiments into reliable product capabilities. Who are you? • 5+ years of industry experience in data science, applied machine learning, or AI engineering. • 5+ years of hands-on Python experience, including building and maintaining production services, with strong practices in software design, testing, code review, and debugging. • Ability to translate ambiguous product and clinical needs into maintainable technical solutions and measurable success criteria. • Proven experience owning AI solutions end to end, from problem definition and experimentation to deployment, monitoring, and ongoing improvement. • Hands-on experience building production LLM applications, including prompt design, structured outputs, and conversational or agentic workflows. • Experience designing LLM evaluations, including trusted evaluation datasets, LLM-as-a-judge methods, and systematic error analysis. • Practical experience developing and deploying applications on cloud platforms such as AWS, GCP, or Azure. How will you contribute? • Build and own production AI capabilities for clinical documentation, structured information extraction, clinical insights, chat experiences, and AI agents. • Develop reusable LLM workflows and services, including prompt components, retrieval, and tool integrations that support diverse clinical use cases. • Drive measurable quality improvements through evaluation datasets, automated testing, clinical feedback, and investigation of real-world failure patterns. • Make AI reliable at scale, balancing accuracy, consistency, latency, and cost, and owning improvements from experimentation through production monitoring. • Shape technical and product direction alongside engineering, product, and clinical experts; mentor colleagues and equip teams with tools to build and evaluate AI confidently. What qualifications and skills will help you to be successful? Some nice to haves are • Experience building AI applications, agents with tool use, context management, and multi-step workflows. • Experience with audio or multimodal models, speech-to-text, or speaker diarization. • Experience with healthcare applications, sensitive data, or multilingual NLP. • Experience working in a startup environment. • A master’s or Ph.D. in Computer Science, Statistics, Machine Learning, or a related field. This is a unique opportunity to join a startup that is having a meaningful impact on the well-being and mental health of thousands. We have • A product that positively impacts peoples' lives every single day. • A team of amazing people with a shared vision and the infinite drive to make it happen • We offer significant equity. • Opportunity to build, grow and become highly instrumental in shaping how technology can increase the effectiveness of therapy. • Hybrid work opportunities. • Mental health days off you can take any given moment simply because you need them.

Description Pango is looking for an experienced Data Scientist to join us and take a key role in turning large-scale, real-world data into smarter product and business decisions.With millions of users interacting with Pango's mobility services, our data reflects complex customer behavior, business models, and real-life mobility patterns.We're looking for someone who can go beyond building models — someone who knows how to identify the right problems, challenge assumptions, uncover opportunities in the data, and translate them into real business impact. You'll have significant professional ownership, from taking an ambiguous business question and framing it as a statistical or Machine Learning problem, through choosing the right methodology, building and evaluating the solution, and bringing it to production.Just as importantly, we expect you to proactively identify questions that should be answered with data — even when nobody has asked them yet. Responsibilities • Own Data Science problems end-to-end — from business question and hypothesis to modeling, evaluation, and production. • Partner closely with Product, Business, Data, and Engineering teams to translate complex business challenges into data-driven solutions. • Proactively identify opportunities where statistical analysis, Machine Learning, and AI can improve our products, customer experience, and business performance. • Build, train, evaluate, and improve Machine Learning models used in production, across both real-time and batch use cases. • Select the right statistical or ML approach based on the problem and the data — including recognizing when a simple analytical solution is better than a complex model. • Define meaningful evaluation methodologies and connect model performance to real business impact. • Communicate complex statistical findings clearly to both technical and non-technical stakeholders. Requirements • 4–6 years of hands-on experience as a Data Scientist. • Strong statistical foundation and hands-on experience with Machine Learning. • Strong experience with Gradient Boosted Trees, such as XGBoost, LightGBM, or CatBoost. • Hands-on experience with AI technologies, including Generative AI and foundation models, as part of real-world solutions. • Strong Python and SQL skills. • Experience developing and deploying models in a production environment. • B.Sc. or M.Sc. in Statistics, Applied Mathematics, Physics, Electrical Engineering, Computer Science, or a related quantitative field. Advantages • Experience with production ML platforms such as AWS SageMaker. • Experience with real-time and batch inference. • Experience with neural networks, sequence models, and embeddings. • Experience working in a large-scale B2C or data-rich product environment.

Description Sentra is the global leader in cloud-native data security for the AI era. The company’s mission is to empower organizations to confidently scale their data operations across multi-cloud and on-premises environments while leveraging the power of AI without compromising security. Sentra’s unique approach enables enterprises to autonomously scan their environments without the need for agents, ensuring that data remains securely within their cloud or on-premises infrastructure. This innovative methodology sets us apart in the industry, providing organizations with control and visibility over their sensitive data at all times. Our commitment to excellence in data security posture management and data detection and response makes Sentra a leader in the field. We are seeking an experienced Data Science Team Lead to join us and play a key role in shaping the future of data security. As a Data Science Lead, you will be part of Sentra’s Classification team, which lies at the core of our mission - identifying sensitive data and helping customers detect the most critical risks in their cloud environments. Our multidisciplinary team of data scientists. Responsibilities • Lead the end-to-end lifecycle (design, development, and deployment) of ML models (e.g., NER, LLMs) to advance our data classification and entity recognition capabilities. • Partner with Product to align cutting-edge AI technologies with real-world customer needs and Sentra’s roadmap. • Architect robust experimentation frameworks to accelerate model iteration, validation, and production deployment. • Utilize extensive datasets to define quality benchmarks and drive continuous performance improvements. • Champion innovation by identifying opportunities for automation and AI-driven features that maximize customer value. Requirements • 7+ years of DS experience, with deep expertise in NLP and/or Generative AI. • 3+ years leading DS teams (managing 3+ ICs), with a focus on team growth and mentorship. • Proven track record of scaling ML models in production environments. • Strong proficiency in Python, SQL, and modern ML frameworks. • Hands-on experience with Big Data technologies, MLOps, and cloud-based AI infrastructure. • Strategic mindset, with experience managing technical debt and defining long-term research roadmaps in Agile environments. • Excellent communication skills, capable of translating complex technical insights for diverse stakeholders. Nice to have: • Prior experience in the data security or the compliance industry. • Experience processing large amounts of data using Big Data tools like Spark. • Experience using cloud based fine tuning frameworks. • A Master’s or Ph.D. in a relevant field (e.g., Data Science, Computer Science, Statistics, Mathematics) is preferred.

About Fundamental Fundamental is an AI research lab pioneering the future of enterprise decision-making. Our flagship model, NEXUS is the world's most powerful Large Tabular Model (LTM) - purpose-built for the structured records that contain trillions of dollars in business value. With $275m in funding from leading investors and trusted by Fortune 100 companies, Fundamental is giving businesses the Power to Predict. At Fundamental, you'll work on unprecedented technical challenges in foundation model development and build technology that transforms how the world's largest companies make decisions. This is your opportunity to be part of a category-defining company from the ground-up. Join the team defining the future of enterprise AI. About the role In this role, you'll research, develop, and productize data science capabilities that enhance and expand our product performance on real enterprise use cases - working across a wide range of prediction tasks, data types, and business domains. You'll go deep on hard data science problems, collaborate closely with R&D on product capabilities, and ship production-grade work that has a direct impact on Production use cases. Key responsibilities • Research and develop data science methods that improve NEXUS predictive performance across diverse enterprise datasets, industries, and prediction task types • Design and implement robust, production-quality Python components with a strong focus on correctness, generality, and reusability • Deeply understand the characteristics of real-world enterprise data and develop strategies that help NEXUS handle them reliably • Run rigorous experiments to measure the impact of new approaches, design meaningful benchmarks, and use results to guide prioritization • Work across a wide variety of structured data problems - including but not limited to classification, regression, ranking, and forecasting • Collaborate closely with the Engineering and Research teams to develop a deep understanding of NEXUS model behavior and use that knowledge to inform your work • Work with Applied AI Engineers to validate approaches on real customer datasets and translate findings into product capabilities • Contribute to technical documentation and internal best practices, helping the broader team apply new capabilities correctly and confidently Must have • 5+ years of experience in data science or machine learning roles • Strong Python skills, including fluency with pandas, numpy, and scikit-learn • Deep hands-on experience with traditional ML models: XGBoost, LightGBM, CatBoost, and similar gradient boosting frameworks • Solid understanding of what makes real-world tabular data challenging: class imbalance, high cardinality, distribution shift, missing values, and more • Strong experimental mindset - comfortable designing benchmarks and drawing rigorous conclusions from noisy results • Ability to work autonomously and drive work from idea to shipped output Nice to have • Familiarity with tabular foundation models (TabPFN, CARTE, or similar) • Competitive data science experience (Kaggle, DrivenData, or similar) - especially top finishes on tabular competitions • Background in a domain where structured prediction matters: finance, supply chain, healthcare, retail, or industrial • Experience contributing to or designing internal ML libraries or shared tooling • Familiarity with DuckDB, Polars, or modern in-process analytics engines • Comfort reading ML research papers and translating findings into practical implementations Benefits • Competitive compensation with salary and equity • Comprehensive health coverage for you and your dependents • Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys • Relocation support for employees moving to join the team in one of our office locations • A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action

Description A growing B2B SaaS company is looking for an experienced Head of Data Science to lead its Data Science function and drive the next generation of AI and machine learning capabilities. This is a strategic leadership role combining people management, hands-on problem-solving, cross-functional collaboration, and ownership of data-driven innovation across the organization. Responsibilities • Lead and mentor a global team of Data Scientists • Define and execute the company's Data Science strategy • Drive the development of advanced machine learning, optimization, and forecasting solutions • Partner closely with Product, Engineering, Customer Success, and executive leadership • Translate complex business challenges into scalable analytical solutions • Support customer-facing initiatives and strategic engagements when needed • Establish best practices for experimentation, model evaluation, and performance measurement • Act as a key stakeholder in shaping the company's AI vision and roadmap Requirements • 8+ years of experience in Data Science, Machine Learning, Statistics, Operations Research, Economics, or a related field • Proven experience leading Data Science teams • M.Sc. or Ph.D. in a quantitative discipline • Strong expertise in machine learning, predictive analytics, optimization, forecasting, and statistical modeling • Experience in fintech, revenue optimization, forecasting, recommendation systems, retail technology, or similar data-intensive domains • Strong business orientation and ability to connect analytical insights to business outcomes • Excellent communication and stakeholder management skills • Experience working in a SaaS environment • Fluent English Advantage • Experience with Generative AI and LLM-based applications • Experience working with enterprise customers • Experience managing distributed teams

Description Join Personetics as an Intermediate Applied Data Scientist, where you'll work with a dynamic team to analyze complex data and deliver innovative solutions for our clients. Utilize your expertise to drive data-driven decision-making and support the development of cutting-edge financial technology. About the position We are hiring an Applied Data Scientist to build the models that turn raw transaction data into the insights our banks’ customers see every day. The stack is deliberately wide: classical ML on tabular data, deep learning, LLM-based systems, and agentic flows. We choose the right approach for each problem, balancing analytical quality, production readiness, and time to market. You drive the analytical work, working closely with Product and Engineering to take ideas from evidence through production. Responsibilities • Analyze and interpret complex datasets to identify trends and patterns. • Collaborate with cross-functional teams to develop data-driven solutions. • Build and maintain predictive models to enhance business decisions. • Communicate findings and insights effectively to stakeholders. • Stay updated with the latest data science technologies and methodologies. • Contribute to the continuous improvement of data processes and systems. Requirements • Bachelor's degree in Data Science, Computer Science, or related field. • 3+ years of experience in applied data science or a similar role. • Proven experience with machine learning algorithms and statistical modeling. • Proficiency in programming languages such as Python or R. • Strong analytical skills and ability to work with large datasets. • Excellent communication and teamwork skills. • Experience with data visualization tools like Tableau or Power BI. Nice to have • FinTech or banking experience. • Transformer models — fine-tuning and production inference. • Experience taking a model into production, including monitoring and post-launch iteration. • Cloud platforms (AWS, Azure).

Description Join Noma Security and help shape the future of AI security in a fast-paced, high-impact environment. Noma is building the first comprehensive AI Security and Governance Platform, helping organizations adopt AI and LLMs with confidence and control. As AI becomes core to modern enterprises, we provide seamless visibility and protection across the entire AI lifecycle. Our team works at the intersection of AI, security, and cloud, shaping a new category in a rapidly evolving market. At Noma, you’ll have the opportunity to make a meaningful impact while working with exceptional people on technology that truly matters. We’re looking for a Senior Data Scientist to be a core driver in how our product empowers security teams. You will be expected to deeply understand customer needs and translate them directly into product features that deliver real value. You'll own key parts of our frontend stack, drive key architectural decisions, and turn complex security data into clear, actionable business insights. In this role, you will design, build, and productionize advanced models that help organizations secure AI systems across data, models, and runtime usage. You’ll work closely with Product, Engineering, and Security teams to turn complex, real-world security problems into scalable, high-impact AI solutions. This is a high-impact, hands-on role with true ownership, where your work directly shapes the intelligence powering a category-defining AI Security platform. 🛠️ What You’ll Do: • Own End-to-End Model Development (Research → Production) • Take full ownership of the model lifecycle: problem definition, research, prototyping, training, evaluation, deployment, and ongoing optimization. • Design and build scalable ML / AI solutions to detect, analyze, and mitigate AI-related security risks. • Ensure models are robust, explainable, and production-ready in real-world enterprise environments. • Partner Deeply with Product & Engineering • Collaborate closely with Product Managers to translate customer pain points and security requirements into clear modeling objectives. • Work hands-on with engineering to integrate models into production systems and data pipelines. • Balance research depth with pragmatic execution and business impact. • Build AI Security Intelligence • Develop capabilities across areas such as AI behavior analysis, anomaly detection, model governance, data risk detection, and usage observability. • Work with structured and unstructured data, including logs, prompts, model outputs, and metadata. • Continuously iterate on models based on usage patterns, feedback, and emerging threat vectors. • Lead Research POCs & Innovation • Stay at the forefront of LLMs, applied ML, and AI security techniques and bring new ideas into the product. ✅ What You Bring: • 5+ years of experience in Data Science or Applied ML roles. • 3+ years of backend development experience, working with production systems. • Strong hands-on experience with language models / LLMs and modern ML techniques. • Bachelor’s degree in Computer Science (or equivalent practical experience). • Proven experience owning end-to-end research POCs, from ideation to real-world impact. • Strong understanding of product and business value, with a bias toward lean, effective solutions. • Deep understanding of language models 🎯 Nice to Haves • Experience in AI security, application security, or threat detection. • Background in LLM workflows, RAG pipelines, prompt analysis, or multi-model systems. • Experience building internal platforms or developer-facing ML tooling. • Previous experience in leadership roles such as Tech Lead or Team Lead. • Startup experience, especially in early or growth-stage companies. 💙 Perks & Benefits • Located in a prime area with easy access to public transportation, near the Hashalom train station and the Light Rail. • A bright, spacious, dog-friendly office that makes you smile the moment you walk in 🐶 • Team bonding activities, company retreats, happy hours, and holiday gifts • Pilates classes at the office 💪🧘‍♀️ • Never hungry: Monthly lunch budget, dinners provided, and a fully stocked kitchen 🍽️ • A warm, supportive, and people-first company culture • Pension & Keren Hishtalmut (advanced training fund) • A global work environment with teams across Tel Aviv, the US, the Netherlands, and London • Options that let you share in Noma’s growth and success About The Company Noma is building the industry's first application security platform built to secure the Data & AI Lifecycle—from development to production and from classic data pipelines and ML to GenAI. Our mission is to create a common language between data science and application security teams, helping them secure AI-powered apps without slowing down AI innovation. In just a year, we've helped our customers, including Fortune 500 companies, secure and protect their entire Data & AI Lifecycle with our holistic platform.

We offer the industry’s only platform that fuses customer identity and anti-fraud solutions – customer identity management, identity verification, and fraud prevention. We sell to industries with large, consumer-facing businesses such as: banking, financial services, insurance, fintech, gaming, ecommerce/retail, telco / media, utilities, etc. About the Role: Transmit Security is a top player in its game and is heading for an exciting year. In this role, you will take an integral part in the creation of a new and innovative SaaS product. If you are a talented software engineer and engineering manager that likes to solve complex problems and looking for your next challenge we want you to join our team! What you’ll do: As the Team Leader of a Detection and Response Engineering team at Transmit Security, you will lead a talented team to design, implement, and deploy scalable data solutions for an innovative SaaS product. You’ll be responsible for shaping the direction of a system that impacts millions of users worldwide. If you're an experienced manager with a strong technical background, ready to lead in a dynamic, fast-paced production environment, we want you on our team! The group responsible for 4-5 different products: 1. DRS (fully managed fraud detection solution) 2. Agentic Visibility 3. Citadel (ITP) - lean version of DRS capabilities 4. Transaction Monitoring offering 5. More might come soon Responsibilities: • Lead and guide one of the DRS Engineering teams in the design and deployment of scalable data infrastructure. • Collaborate effectively with cross-functional teams (Data Science, Research, Security, etc.) to ensure alignment on business needs and security standards. • Manage the technical backlog, make critical decisions on product milestones, and ensure timely, secure, high-quality delivery and deployment. • Foster the growth of team members through mentorship, personal development opportunities, and the promotion of continuous improvement. • Identify, manage, and mitigate security risks across the data platform, maintaining high standards in all initiatives. • Define and implement methodologies to guarantee the performance, scalability, and quality of our data infrastructure. What you’ll need: • 5+ years of software engineering experience, with at least 2 years in a leadership capacity. • Advantage: and cloud platforms (AWS, GCP, Azure). • Proficiency in programming languages such as NodeJS, Python, Java, Scala, or Go. • Familiarity with databases (Postgres SQL, Redis) and Kubernetes. • Demonstrated strong leadership abilities, including guiding teams, managing backlogs, and fostering effective cross-functional collaboration. • Proven experience in managing security risks and ensuring high-quality, scalable, and compliant systems. • Ability to maintain focus on key priorities and excel in a fast-paced, dynamic production environment. • For Data-Science - looking for an Engineering Team lead with a past knowledge / experience in data-science teams. Advantages: • Bachelor’s degree in Computer Science or a related field. • Extensive knowledge of distributed computing platforms (Flink, Spark, Beam) • Experience with microservice architecture, data management tools (Kafka, Airflow, MLOps), and CI/CD processes. • Background in identity management, risk assessment, or fraud detection. #LI-TL1 #LI-Hybrid

About Tavily: We're building the infrastructure layer for agentic web interaction at scale. Our API is designed from the ground up to power Retrieval-Augmented Generation (RAG) and real-time reasoning in AI systems. By connecting LLMs to high-quality, trustworthy web content, we help developers build agents that are not only intelligent — but also informed. We work with some of the most innovative teams in AI — from small startups shaping the ecosystem to the largest enterprises deploying AI at scale. Whether it's powering sales assistants, research copilots, or internal knowledge tools, we're the missing link between LLMs and the real world. The Role: Data Scientist: We are hiring a Data Scientist to join our data team, which plays a central role in shaping cross-company decisions across GTM, Product, and Business functions. Responsibilities: • Develop, implement, and maintain machine learning models on business-related data • Apply statistical methods to analyze large, complex datasets and extract actionable insights • Partner with stakeholders across Product, GTM, and Business teams to identify opportunities and solve high-impact problems • Support deployment, evaluation, and monitoring of models in production environments Requirements: • 3+ years of experience in Data Science • Strong statistical background • Solid understanding of classical machine learning models and algorithms • Experience working with business data (e.g., product, marketing, revenue, user behavior) • Proficiency in Python and SQL • Experience with modern AI coding tools (e.g., Claude Code, Cursor) • Experience working with Git Tech stack: • Data warehouses and platforms such as Snowflake and/or Databricks – required • Experience working in modern data environments and pipelines Education: • Bachelor’s degree in Statistics, Mathematics, Computer Science, or a related field – required • Master’s degree in a relevant field – preferred Preferred qualifications: • Experience working in production environments • Strong problem-solving skills and ability to work in a cross-functional environment • This role is ideal for someone who wants to work at the intersection of data, product, and business, and have a direct impact on company-wide decisions.

Ambition Needs a Place to Grow. At Playtika, we create mobile games enjoyed by millions worldwide. Combining the scale of a public company (NASDAQ: PLTK) with the speed and ownership of a startup, we are a global leader where innovation, data, and creativity shape the future of entertainment. Here, your ideas matter, your decisions impact products, and your growth is supported across global studios. Bring your hunger where it belongs: at the front of the pack. Playtika is looking for a Principal Data Scientist to join the Data & AI Department and shape the scientific direction of our work across the player experience. This position is based in Herzliya, Israel. We are looking for people with exceptional soft skills and outstanding hard skills. We love to address complex intellectual challenges and make sense of high dimensional and dynamical data that impact the game experience of millions of players. You will join a multidisciplinary team with a variety of business use-cases and algorithmic approaches, and you will help shape its scientific direction. We use strong statistical fundamentals with SOTA algorithms and cutting-edge technologies to provide a better experience for our players. Our solutions translate directly to production (mostly as part of a product) and serve the business needs from different use-cases & multiple studios. The problems are varied and rigorous: understanding and predicting player behavior, optimization of game mechanics, causal inference and online experimentation, sequential decision-making with bandits and RL, and more. We care about what works in practice, not only what works on a benchmark. Responsibilities • Conduct full data driven research and solution development including problem definition, data collection and validation, model development, evaluation, and deployment • Set the technical direction and roadmap for data science across multiple studios and use-cases, and influence senior stakeholders on research priorities • Own and demonstrate the business impact of your solutions in a live production environment • Collaborate with cross-functional teams (business, engineers, BI, product) to develop, test, and deploy your models quickly and effectively • Drive and contribute to scientific papers, blogs, conferences, etc., representing Playtika in the wider data science community • Mentor and coach DS/MLE colleagues, including senior team members, and act as the lead DS Subject Matter Expert within the organization Qualifications • M.Sc. or Ph.D. in Computer Science, Mathematics, Statistics, Engineering or a related field • 8+ years of work experience, including a proven track record of leading complex data science initiatives end to end • Exceptional problem-solving and scientific reasoning skills, including knowing which problems are worth solving and which methods fit them • Deep theoretical and practical knowledge of machine learning, with recognized expertise in one or more areas (e.g., causal inference, LTV/churn prediction, experimentation, personalization) • Strong Python and SQL, and fluency with AI-assisted development tools (Cursor, Claude Code, etc.) that make you faster • Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical audiences (e.g., product managers, business domain experts, executives) • Ability to influence without authority and lead across teams • A team-player mindset Nice to have • RL background (e.g. multi-armed bandits) – strong advantage • Working experience of Git • Experience in the gaming industry We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Subject to applicable laws, we may use artificial intelligence (AI) tools to assist our recruitment teams in the hiring process, including drafting job descriptions, communication, response to applications, assessments and tests, as further described in our Candidates Privacy Notice. By applying to this job, you acknowledge that you have read and understood our Candidates Privacy Notice, including with respect to the use of AI tools, and consent to the processing of your information as described therein. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you feel the above describes you perfectly - Apply now! Employee at Playtika? Click here

Description About Us Arpeely is bootstrapped and has been profitable since day one. We built one of the most efficient programmatic acquisition engines on the planet: processing billions of ad decisions a day, generating terabytes of live behavioral data, and turning it into margins most SaaS companies would kill for. At the core of that engine is a team of data scientists and ML engineers running tens of billions of sub-second predictions a day, deciding in milliseconds which impression is worth buying and what it’s worth. Now we’re taking everything we’ve learned about how people move through the web and putting it into our most innovative consumer product yet: Ace AI, an AI-native browser already reaching millions of people, built to simplify and improve everyday online life with the help of AI. This is a rare opportunity: a category that hasn’t meaningfully changed in over a decade, and a profitable company with the data and the acquisition engine to win it on its own terms. Come build it with us. What You’ll Do • Mentor a team of extremely talented and success-hungry data scientists. • Initiate and manage cutting-edge projects from inception to delivery, including developing structured and automated solutions. • Lead the data strategy: be responsible for planning, prioritizing, and building the right data solutions to support business needs. • Apply your scientific knowledge and creativity to analyze large volumes of diverse data and develop algorithmic solutions and models to solve complex problems. • Identify and propose data science and algorithmic solutions for various product initiatives. • Use your excellent communication skills, both written and verbal, to explain technical concepts and analysis implications to senior leaders, and influence cross-functional teams to improve performance. • Partner with other departments (e.g. Management, R&D, Product) to support decision making. Requirements • Two years of experience in leading a team. • 4+ years of practical analytics experience in big data businesses (preferably at a B2C company). • A hands-on, passionate person who likes to get to the bottom of things in terms of algorithms, data, and business. • Excellent analytical skills with experience in querying large, complex data sets. • Strong understanding of statistical significance. • Hands-on experience with machine learning algorithms; Python and data visualization tools such as Tableau, Looker, etc. • BSc degree (or higher) in Mathematics, Statistics, Engineering, Computer Science, or any other quantitative field. • Self-learner, multi-tasker, able to work independently. • Self-sufficient, proactive problem-solver. • Excellent communication skills, both written and verbal. • Familiarity with the ad-tech industry — a big plus. • Experience in implementing real-time machine learning and data mining algorithms in large-scale environments — a big plus. • Fun to work with and a team player :)

Description Vega is one of the fastest-growing startups in cybersecurity, redefining security analytics and operations with an AI-native platform for the SOC. We are building the next-generation operating system for security teams. Vega is already delivering real impact at some of the world’s largest organizations - improving detection, unlocking the value of their security data, and reducing cost and complexity. With HQs in New York and TLV, we're looking for people who want to be a part of the next rocket-ship in cyber. We're looking for a Data Scientist to join our team. As a Data Scientist at Vega, you’ll be a key member of our AI team, designing, building, and deploying cutting-edge AI systems that leverage large language models (LLMs), unstructured data, and advanced ML techniques. You’ll be instrumental in bringing AI from research to real-world production, delivering high-impact features that drive our security platform. In this role, you'll have a unique opportunity to solve complex problems, work with large scale data and be part of the core team that shapes the future of AI in the company. WHAT YOU WILL DO • Design and develop end-to-end AI solutions, from data ingestion and modeling to deployment and observability. • Build and fine-tune LLM-based applications to tackle complex cybersecurity challenges. • Own the full ML lifecycle — from ideation and experimentation to production readiness. • Collaborate with product, engineering, and security teams to turn AI research into user-facing features. • Work with large-scale unstructured data (e.g., logs, threat intel, alerts) to extract meaningful insights. • Evaluate and optimize AI system performance, scalability, and reliability. • Contribute to core architectural decisions related to AI and ML infrastructure. Requirements WHAT YOU WILL BRING • 4+ years of professional experience in ML/AI engineering. • Hands-on experience working with LLMs and building AI agents in production environments. • Strong understanding of text classification, ranking, and evaluation in NLP systems. • Proficiency in Python and modern ML frameworks. • Deep knowledge of deploying and maintaining AI systems at scale. • Experience with cloud platforms, particularly AWS. • Experience working independently in fast-paced, mission-driven environments • Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field NICE TO HAVE • Experience fine-tuning LLMs for domain-specific or task-specific use cases. • Background in cybersecurity applications (e.g., threat detection, incident response, log analysis). • Familiarity with agent-based architectures and autonomous systems.

About Us Riskified empowers businesses to unleash ecommerce growth by taking risk off the table. Many of the world’s biggest brands and publicly traded companies selling online rely on Riskified for guaranteed protection against chargebacks, to fight fraud and policy abuse at scale, and to improve customer retention. Developed and managed by the largest team of ecommerce risk analysts, data scientists and researchers, Riskified’s AI-powered fraud and risk intelligence platform analyzes the individual behind each interaction to provide real-time decisions and robust identity-based insights. Riskified is proud to work with incredible companies in virtually all industries including Booking.com, Acer, Gucci, Lorna Jane, GoPro, and many more. We thrive in a collaborative work setting, alongside great people, to build and enhance products that matter. Abundant opportunities to create and contribute provide us with a sense of purpose that extends beyond ourselves, leaving a lasting impact. These sentiments capture why we choose Riskified every day. About the Role The Data Science department powers Riskified’s core engine by building production-grade algorithmic solutions at immense scale. As a Staff Data Scientist on the Identity team, you will drive the innovation roadmap for our Identity Graph Engine. You will architect, research, and deploy state-of-the-art machine learning models - spanning graph neural networks, transformers, and deep tabular architectures - to solve complex entity resolution and fraud prevention challenges at scale. What You'll Be Doing • Drive Identity Graph Innovation: Architect and advance the next generation of our Identity Graph Engine using state-of-the-art graph models, transformers, and machine learning techniques. • Technical Leadership: Define the research roadmap for identity resolution, setting technical standards and guiding complex research projects from initial concept to high-throughput production systems. • Large-Scale Modeling: Build scalable predictive and representation-learning models over massive tabular, sequence, and graph-structured datasets. • Cross-Functional Architecture: Collaborate closely with Data Engineering, Core Software, and Product teams to seamlessly integrate complex ML pipelines into real-time production environments. • Mentorship & SOTA Research: Benchmark and import cutting-edge academic research into practical business solutions while mentoring senior data scientists on modern modeling paradigms. Qualifications • Education: M.Sc. or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field. • Experience: 6+ years of hands-on experience designing, training, and deploying complex machine learning models in large-scale production environments. • Deep Learning & SOTA Models: Proven expertise with Transformers, Deep Neural Networks (DNNs), Graph Neural Networks (GNNs), or Advanced Tabular Learning architectures. • Big Data Ecosystem: Strong practical experience working with large-scale distributed data processing systems (e.g., Spark, Databricks) and graph databases/frameworks. • Technical Influence: Proven track record of technical leadership, setting architectural direction, and translating complex business requirements into high-impact algorithmic solutions. Advantages • Experience in fraud detection, risk management, or fintech. • Experience in Identity Resolution, Entity Disambiguation, Link Analysis, or Complex Network Modeling. Life at Riskified We are a fast-growing and dynamic tech company with 750+ team members globally. We value collaboration and innovative thinking. We’re looking for bright, driven, and passionate people to grow with us. Our Tel-Aviv team is currently working in a hybrid of remote and in-office work. We have recently moved to our new space in Tel Aviv - check it out here! Some of our Tel Aviv Benefits & Perks: • Equity for all employees, Keren Hishtalmut, pension • Private medical insurance, extra time off for parents and caregivers • Commuter and parking benefits • Team events, fully-stocked kitchen,lunch stipend, happy hours, yoga, pilates, functional training, basketball, soccer • Wide-ranging opportunities to volunteer and make an impact • Commitment to your professional development with global onboarding, skills-based courses, lunch & learns • Awesome Riskified gifts and swag! In the News Geektime: Riskified Goes Public Walla!: Happy Hour at the Riskified Offices Geektime Insider: A look at Riskified Tel Aviv Globes: Riskified to contribute the highest amount up to date to Tmura Globes: Riskified is among Israel’s fastest growing companies TechCrunch: Riskified Prevents Fraud on Your Favorite E-commerce Site Riskified is deeply committed to the principle of equal opportunity for all individuals. We do not discriminate based on race, color, religion, sex, sexual orientation, national origin, age, disability, veteran status, or any other status protected by law.

About Us Riskified empowers businesses to unleash ecommerce growth by taking risk off the table. Many of the world’s biggest brands and publicly traded companies selling online rely on Riskified for guaranteed protection against chargebacks, to fight fraud and policy abuse at scale, and to improve customer retention. Developed and managed by the largest team of ecommerce risk analysts, data scientists and researchers, Riskified’s AI-powered fraud and risk intelligence platform analyzes the individual behind each interaction to provide real-time decisions and robust identity-based insights. Riskified is proud to work with incredible companies in virtually all industries including Booking.com, Acer, Gucci, Lorna Jane, GoPro, and many more. We thrive in a collaborative work setting, alongside great people, to build and enhance products that matter. Abundant opportunities to create and contribute provide us with a sense of purpose that extends beyond ourselves, leaving a lasting impact. These sentiments capture why we choose Riskified every day. About the Role The Data Science department powers Riskified’s core value engine by building scalable, production-grade ML solutions that protect revenue and automate complex decisions. We leverage diverse analytical techniques - from advanced statistical modeling and graph theory to classic machine learning and deep learning - to extract maximum signal from complex datasets. As a Data Scientist, you will own projects end-to-end: framing business problems, developing models, and deploying them to production. This role demands strong quantitative fundamentals, deep machine learning expertise, and a pragmatic problem-solving mindset to translate raw data into real business impact. What You'll Be Doing • End-to-End ML Development: Design, train, evaluate, and optimize scalable predictive models (classification, regression, clustering, deep learning) for complex business challenges. • Data & Feature Engineering: Clean, transform, and extract high-value features from large-scale structured and unstructured data to continuously boost model performance. • Collaboration & Production: Work within the Data Science team and alongside Data Engineers, Developers, and Product Managers to deploy models into production and translate complex insights into clear business actions. • Innovation & GenAI: Continuously explore emerging ML techniques, state-of-the-art tools, and GenAI workflows to elevate the team's analytical capability. Qualifications • M.Sc. in Computer Science, Electrical Engineering, or a related quantitative field. • 2+ years of industry experience developing and deploying machine learning models in production environments. • Deep theoretical understanding and practical experience of ML algorithms on tabular and structured data. • Proactive team player with a strong curiosity and enthusiasm for adopting modern GenAI developer tools. • Proficiency in Python, SQL, and standard ML frameworks. • Strong hypothesis-driven problem-solving skills. • Excellent communication skills, with the ability to explain complex quantitative concepts to non-technical stakeholders. • Direct experience in risk management, e-commerce fraud detection, or fintech domains.Excellent communication skills, with the ability to explain complex quantitative concepts to non-technical stakeholders- Advantage Life at Riskified We are a fast-growing and dynamic tech company with 750+ team members globally. We value collaboration and innovative thinking. We’re looking for bright, driven, and passionate people to grow with us. Our Tel-Aviv team is currently working in a hybrid of remote and in-office work. We have recently moved to our new space in Tel Aviv - check it out here! Some of our Tel Aviv Benefits & Perks: • Equity for all employees, Keren Hishtalmut, pension • Private medical insurance, extra time off for parents and caregivers • Commuter and parking benefits • Team events, fully-stocked kitchen,lunch stipend, happy hours, yoga, pilates, functional training, basketball, soccer • Wide-ranging opportunities to volunteer and make an impact • Commitment to your professional development with global onboarding, skills-based courses, full access to Udemy, lunch & learns • Awesome Riskified gifts and swag! In the News Geektime: Riskified Goes Public Walla!: Happy Hour at the Riskified Offices Geektime Insider: A look at Riskified Tel Aviv Globes: Riskified to contribute the highest amount up to date to Tmura Globes: Riskified is among Israel’s fastest growing companies TechCrunch: Riskified Prevents Fraud on Your Favorite E-commerce Site Riskified is deeply committed to the principle of equal opportunity for all individuals. We do not discriminate based on race, color, religion, sex, sexual orientation, national origin, age, disability, veteran status, or any other status protected by law.

AppsFlyer is a cutting-edge technology company that specializes in mobile attribution and marketing analytics. We run at a massive scale- t any given moment thousands of servers are consuming 150+ billion mobile app events, crunching our users’ data, serving requests and communicating on a massive scale. Fueled by the AppsFlyer platform, Protect360 is the leading anti-fraud solution in the market, protecting advertisers from fraudulent traffic and saving millions of dollars for our customers. We detect fraudulent traffic (fake installs and attribution hijacking attempts) in real time using machine learning, deep learning, and advanced AI techniques applied on massive data streams. We’re looking for a data scientist to join our team and further improve fraud detection capabilities. This position involves analyzing evolving fraud patterns, developing and deploying advanced prevention components, and leveraging domain expertise, data tools, and modern AI methods to stay ahead of emerging threats. A partial list of our tech stack: Python (and its related scientific stack), Spark, TensorFlow/PyTorch, Kafka, AWS services, Airflow, Scala, BigQuery, and more What you'll do • Mine massive data sets to uncover fraud patterns and prevention opportunities. • Develop and productionize large-scale ML, DL, and AI models to detect and prevent fraudulent activity. • Translate business and product needs into scientific, explainable, and high-impact solutions. • Design and maintain end-to-end ML pipelines - from data ingestion and feature engineering to serving and monitoring in production. • Collaborate closely with product, engineering, and business teams to drive data-driven decisions. • Stay current with AI and ML research and evaluate new technologies to strengthen Protect360’s algorithms. What you have • M.Sc in Computer Science, Mathematics, Statistics, Engineering or a related field • 5+ years of experience in applied Data Science or Algorithmic Development, preferably in large-scale production environments. • Hands-on experience in training and fine-tuning machine learning, deep learning, and AI models • Strong programming skills in Python and proficiency in SQL. • Solid understanding of data pipelines, MLOps practices, and working with huge datasets. • Ability to mentor, collaborate, and communicate complex ideas clearly to diverse audiences. • A fast learner, problem solver, and end-to-end owner with a strong “can-do” approach. Bonus Points • Experience in the ad-tech industry or with fraud detection systems. • Familiarity with LLMs, generative AI, or representation learning for anomaly detection. • Proven track record working with large-scale distributed data systems. • Being introduced by an AppsFlyer employee As a global company operating from 20 offices worldwide, we reflect the human mosaic of the diverse and multicultural world in which we live. We ensure equal opportunities for all of our employees and promote the recruitment of diverse talents to our global teams without consideration of race, gender, culture, or sexual orientation. We value and encourage curiosity, diversity, and innovation from all our employees, customers, and partners. “As a Customer Obsessed company, we must first be Employee Obsessed. We need to make sure that we provide the team with the tools and resources they need to go All-In.” Oren Kaniel, CEO