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!

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.

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 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 :)

Job Description As a Staff Data Scientist at ServiceNow, you’ll play a highly embedded and influential role within our Data Science organisation, partnering closely with Development and Product teams across multiple products within ITOM. Rather than simply responding to predefined requirements, you’ll bring your own creativity, domain expertise, and ideas to identify opportunities, challenge assumptions, and solve complex problems using real customer data. What you get to do in this role: • Lead the development and evolution of advanced data science and machine learning capabilities, including noise reduction, anomaly detection, root cause analysis, and new AI-powered product features. • Own complex data science problems end-to-end, from problem definition and ideation through experimentation, model development, evaluation, productionization, and deployment. • Develop advanced algorithms and models using techniques such as machine learning, deep learning, NLP, anomaly detection, and statistical modeling. • Partner closely with Product, Engineering, Quality, and Architects to translate product requirements into scalable, reliable ML solutions. • Drive technical direction and mentor other data scientists, contributing to best practices in modeling, experimentation, evaluation, and ML engineering. • Stay current with advances in AI/ML and identify opportunities to apply emerging technologies to ServiceNow products. Qualifications To be successful in this role you have: • Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. • 6+ years of experience in data science, machine learning, algorithm development, or a related field. • Advanced expertise in at least one area such as anomaly detection, machine learning, deep learning/neural networks, NLP, or statistical modeling. • Proven experience leading complex data science or machine learning problems from ideation to production. • Strong Python skills and hands-on experience with modern data science and ML frameworks. • Experience working with large and complex datasets, developing evaluation methodologies, and defining metrics for ML models and data-driven products. • Practical experience with modern AI/ML techniques, including LLMs and/or generative AI. • Strong technical leadership, problem-solving, communication, and cross-functional collaboration skills. Additional Information Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.  Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact [email protected] for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

About Payoneer Founded in 2005, Payoneer is the global financial platform that removes friction from doing business across borders, with a mission to connect the world’s underserved businesses to a rising global economy. We’re a community with over 2,500 colleagues all over the world, working to serve customers, and partners in over 190 countries and territories. By taking the complexity out of the financial workflows–including everything from global payments and compliance to multi-currency and workforce management, to providing working capital and business intelligence–we give businesses the tools they need to work efficiently worldwide and grow with confidence. Senior Data Scientist – AI & ML Hybrid Full-time Role Summary You’ll be one of the founding data scientists on our brand-new ML team, building Payoneer’s AI and data science capabilities from the ground up. Working closely with the Tech Lead, you’ll develop and deploy models across payments, risk and customer analytics, and build the frameworks that evaluate our GenAI and LLM-based agents. You’ll set the modeling standards, technical practices and culture the team will scale on, and help hire the data scientists who come next. It’s a great fit if you’re excited to build something new and own it end to end. What You’ll Do • Build evaluation frameworks for GenAI and LLM agents – golden datasets, LLM-as-judge, and quality, safety and compliance monitoring • Own the full ML model lifecycle, from research and experimentation through production deployment and monitoring • Design and deploy ML models that solve complex business problems across payments, risk and customer analytics • Work with the Tech Lead to define core modeling methodologies, analytical standards and research practices • Set up the team’s approach to feature engineering, model validation, experimentation, A/B testing and performance monitoring • Lead exploratory research to uncover insights, identify ML opportunities and evaluate new techniques • Partner with business stakeholders to translate problems into data science solutions and communicate findings clearly • Shape the team’s culture and documentation standards, and help interview, onboard and mentor new data scientists Who You Are • 5+ years of experience in Machine Learning, Data Science or a related technical role • Proven track record of building and deploying ML models in production environments • GenAI/LLM evaluation experience – benchmark datasets, LLM-as-judge or human-in-the-loop evaluation, and monitoring of RAG and agent systems • Strong proficiency in Python and SQL, and in ML frameworks such as TensorFlow, PyTorch and Scikit-learn • Experience with cloud platforms (AWS, GCP or Azure) and MLOps tools and practices • Technology leadership – a history of making tech stack decisions and establishing development practices that scale • Excellent communication skills, with the ability to explain technical concepts and influence technical decisions • Entrepreneurial, self-starter mindset – excited to build from scratch and comfortable with ambiguity and ownership • Sc. or M.Sc. in Computer Science, AI, Data Science, Mathematics or a related quantitative field • Experience in fintech or financial services – an advantage The Payoneer Ways of Working Act as our customer’s partner on the inside Learning what they need and creating what will help them go further. Do it. Own it. Being fearlessly accountable in everything we do. Continuously improve Always striving for a higher standard than our last. Build each other up Helping each other grow, as professionals and people. If this sounds like a business, a community, and a mission you want to be part of, apply today. We are committed to providing a diverse and inclusive workplace. Payoneer is an equal opportunity employer, and all qualified applicants will receive consideration for employment no matter your race, color, ancestry, religion, sex, sexual orientation, gender identity, national origin, age, disability status, protected veteran status, or any other characteristic protected by law. If you require reasonable accommodation at any stage of the hiring process, please speak to the recruiter managing the role for any adjustments. Decisions about requests for reasonable accommodation are made on a case-by-case basis.