Data Scientist jobs in Tel Aviv-Yafo

Description Applied Data Scientist — Intent Drift Detection Backslash Security · Realtime AI-agent protection About Backslash We are builders who want to secure the next generation of software development from the inside out. Software development has entered a new era defined by vibe-coding, MCP servers, and AI agents. While these tools allow developers to build faster than ever, they also introduce a completely new frontier of security challenges that exist directly on the engineer's machine. Backslash is building the security layer for this new reality. We provide the essential guardrails and visibility needed to secure AI-driven workflows. By actively protecting developer computers and monitoring IDE-based AI interactions, we ensure the future of coding is as secure as it is fast. The Role AI coding agents run with enormous privilege on developer machines. When untrusted content steers one off its task, classical security sees only the final action — never that the agent's intent drifted. Detecting that drift, in realtime, on-device, is an open problem. No one has solved it. You will. You will own intent-drift detection end-to-end — from the data to the model: • Build the Dataset: Design and generate the data that defines what "drift" looks like, and co-design the pipeline that creates it. • Train Small, Ship Local: Fine-tune, distill, and shrink the models that detect drift in realtime — small enough to run fully on-device, no cloud. • Shape the Architecture: Decide what's a model, what's a rule, and what's a gate. The detector's design is your call. • Measure What Matters: Build the evaluation harness — realtime detection at very low false-positive rates on a developer's machine is the product. You own intent-drift analysis as a problem, not a ticket. Requirements • Applied Data Science End-to-End: 3–5 years turning ambiguous problems into working models — problem framing, data collection and labeling strategy, feature/representation design, training, and evaluation. You've owned a dataset and the model that consumed it. • Small-Model Fluency: Comfortable fine-tuning small open models locally — DeBERTa-class encoders, ≤8B decoders, LoRA, quantization, single-GPU workflows. • Applied-Research Mindset: You approach an open research problem with passion and a practical, ship-it attitude. • Independence: You want an impactful, strategic problem in LLM security — not a ticket queue. • Startup DNA: Can-do, fast, a true partner. Non-negotiable. Local-first by design. Python, PyTorch, HuggingFace, ≤8B models. Bonus Points For • Security Background: Prompt injection, MITRE ATLAS, agent security — or the hunger to learn it fast. • Adversarial ML: Experience with LLM evaluation, red-teaming, or building adversarial datasets. • Endpoint Software: Familiarity with software that runs locally on developer machines with a low resource footprint.

Overview Come build community, explore your passions and do your best work at Microsoft with thousands of University interns from every corner of the world. This opportunity will allow you to bring your aspirations, talent, potential—and excitement for the journey ahead.   As a Data Scientist Intern at Microsoft, you will combine applied AI, engineering, and scientific experimentation to build intelligent systems. Your work will focus on developing autonomous AI agents, evaluating large language models (LLMs), and automating research workflows. You will design experiments and apply statistical methods to assess and improve AI systems, accounting for the variability and uncertainty inherent in their non-deterministic behavior. Working with researchers, engineers, product teams, and other stakeholders, you will translate customer and business needs into practical solutions and measurable outcomes. You will combine analytical rigor with hands-on development to build prototypes and evaluation frameworks that improve the quality, reliability, and usefulness of AI-powered experiences. At Microsoft, Interns work on real-world projects in collaboration with teams across the world, while having fun along the way. You’ll be empowered to build community, explore your passions and achieve your goals. This is your chance to bring your solutions and ideas to life while working on cutting-edge technology. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Responsibilities • Develop and improve autonomous AI agents and research workflow automations using LLMs, relevant algorithms, and appropriate data sources. • Explore emerging AI techniques, propose new ideas, and build proofs of concept (POCs) to assess their feasibility, potential value, and limitations. • Design experiments and evaluation frameworks for LLMs and AI agents, applying statistical methods to measure quality and reliability while accounting for non-deterministic behavior. • Explore data, analyze experimental results, and investigate failure modes to identify opportunities, validate approaches, and iteratively improve AI systems. • Communicate findings, limitations, and technical trade-offs clearly, providing actionable insights that inform product and engineering decisions. • Collaborate with researchers, engineers, product teams, and other stakeholders to translate customer and business needs into opportunities to enhance products and customer experiences through applied AI. **This student position is structured as a one-and-a-half-year role, concluding upon completion of the academic degree. Qualifications • Currently pursuing a Master’s degree in Data Science related fields:, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field. • At least 3 additional semesters before graduation – graduation date Winter 2028 or later. • knowledge of or experience working with Large Language Models (LLMs), including areas such as fine-tuning, modeling, evaluation, frontier models, or specialized models. • Hands-on experience writing code in a production environment and working with code repositories (e.g., Git). Preferred Qualifications: • Currently pursuing a PhD in Data Science related fields: Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Overview The WSSI team is looking for a motivated Data Science Intern to contribute to production-oriented AI solutions across computer vision and efficient small language models, helping bring advanced models to Windows products under real-world edge-device constraints.The team’s primary focus is developing state-of-the-art computer vision solutions that can run efficiently under constraints such as model size, latency, power, and deployment efficiency. In this internship, you will work with applied scientists, engineers, MLOps specialists, and data experts to help turn applied research and prototypes into high-quality AI experiences that can create impact for millions of customers. Responsibilities • Contribute to research, training, experimentation, evaluation, and prototyping of AI models in computer vision, efficient small language models, or related applied AI areas. • Support the development of production-oriented AI solutions, with attention to model quality, reliability, scalability, and measurable customer impact. • Analyze model behavior and performance under real-world edge-device constraints, including latency, footprint, power, and resource usage. • Contribute to exploring model optimization techniques including compression and efficient inference to enable deployment in resource constrained environments. • Work with datasets, evaluation pipelines, and experiment tracking to generate clear insights and support data-driven decisions. • Collaborate closely with product, system engineering, software, and silicon teams, and clearly communicate findings, tradeoffs, and recommendations. Qualifications Required Qualifications: • Currently pursuing an M.Sc. or Ph.D. in Computer Science, Electrical Engineering, Data Science, or a related technical field. • Hands-on experience with model development, evaluation, experimentation, and data analysis. • Practical Python development experience, including the use of modern AI-assisted coding tools. Preferred Qualifications: • Experience with computer vision systems, image/video processing, or AI models designed for real-world deployment. • Experience with model optimization, compression, quantization, distillation, efficient inference, or deployment on edge devices. • Experience working with data pipelines, model lifecycle workflows, MLOps concepts, or production AI infrastructure. This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Description Lumenis is a global leader in energy-based solutions for Aesthetics and Eye Care. Headquartered in Yokneam, Israel, with offices in Tel Aviv, Lumenis has a strong global presence and business performance worldwide. We are looking for a Data Insights & Analytics Manager who will develop a deep understanding of data generated by Lumenis' global installed base of connected medical devices, combine it with enterprise data, and translate it into insights and tools that create value for our customers and the business. The role goes beyond reporting and dashboard creation. We are looking for someone who is naturally curious, proactively explores data, identifies patterns and opportunities, and drives the organization to act on what the data reveals. Importantly, the role is expected to uncover broader customer, commercial, and business insights by connecting IoT data with enterprise and other relevant data sources - not only insights derived from device data itself. Main Duties: This is a highly hands-on analytics role at the intersection of data, technology and business, requiring both strong analytical capabilities and a product mindset. Data Foundation & BI • Develop a deep understanding of Lumenis’ IoT data ecosystem, including device events, data structures, business logic, and KPIs. • Work hands-on with data across AWS and enterprise systems. • Partner with BI to define requirements, maintain trusted metrics and models, and improve data quality and usability. • Independently build, maintain, and enhance dashboards and analytics solutions in Amazon QuickSight. Analytics & Insights • You will be expected not only to answer business questions with data, but to identify the questions we should be asking. • Proactively explore complex IoT and business datasets to uncover meaningful trends, patterns, anomalies, and opportunities. • Translate complex data into clear, actionable insights and proactively bring relevant findings to the business. Business & Commercial Analytics • Partner with commercial teams to improve customer engagement, strengthen sales narratives, and develop data-driven tools. • Create compelling, evidence-based data stories for internal and external audiences. • Measure the impact of data-driven initiatives and refine them based on results. Data Activation & Adoption • Drive adoption of analytics tools and data-driven practices across the organization. • Train business users to interpret and apply data effectively. • Proactively communicate relevant insights rather than relying solely on self-service dashboards. • Continuously identify new ways data can create value for customers and the business. Key Interfaces • BI; Sales and Commercial Excellence; Marketing; Service; Product; Finance and Operations; and regional business teams. Requirements • Significant experience in BI, business analytics, data analytics, or a similar role. • Strong SQL skills and hands-on experience with BI platforms such as QuickSight, Power BI, or Qlik. • Ability to independently explore complex datasets and understand data structures, business logic, and KPI definitions. • Strong analytical curiosity, business acumen, and a track record of translating insights into commercial opportunities and actions. • Excellent data visualization, storytelling, communication, and stakeholder-management skills. • A proactive, independent approach, with the ability to drive adoption and influence without formal authority. • Additional advantages include experience with: • IoT, connected-device, or product-usage data. • AWS, S3, Salesforce, SAP, or Python. • Medical devices, healthcare, SaaS, or another connected installed-base business. • Customer-engagement or commercial analytics in a global organization.

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.

Job Description Armis from ServiceNow, protects the entire attack surface and manages an organization’s cyber risk exposure in real time. Combined with ServiceNow’s Security and Risk capabilities, as well as Identity Security capabilities from Veza, we bring together all critical capabilities to secure every asset, every identity - incl. AI Agents - across all environments with the right level of context - security, operational and business - to build the first of its kind autonomous defense platform for the Agentic Enterprise. As an AI-driven cybersecurity company, Machine Learning and Generative AI power the core capabilities that make Armis an industry leader. Our algorithms are the engine behind our advanced Vulnerability Management, Detection, and Remediation (VMDR) platform. We are looking for a Staff Data Scientist with strong Machine Learning foundations and practical enterprise experience to join the VMDR team. In this role, you will act as a technical builder owning complex problem domains end-to-end, diving deep into cybersecurity nuances, and architecting cutting-edge LLM and ML solutions from initial research all the way to scalable production deployment. What You’ll Do • End-to-End Ownership: Drive complex AI and ML initiatives through the full product lifecycle from early-stage prototyping and deep domain analysis to production-grade deployment and monitoring. • Architect & Deploy: Design and build production-ready AI models and system pipelines in Python using modern cloud and big data infrastructure (AWS, Spark). • LLM Innovation: Integrate state-of-the-art Generative AI and LLM workflows directly into our core VMDR features to drive automated detection, prioritization, and remediation insights. • Domain Deep-Dives: Partner closely with domain researchers, data engineers, and product leaders to dive into granular cybersecurity data and translate complex security problems into high-impact AI solutions. Qualifications To be successful in this role you have: • Cybersecurity Background: Domain experience in cybersecurity (specifically Vulnerability Management, Asset Intelligence, or Threat Detection) is a big advantage, but not mandatory. • LLM Expertise: At least 2 years of hands-on experience working with Large Language Models (LLMs), including prompt engineering, fine-tuning, RAG, agentic workflows, and orchestration frameworks (e.g., LangChain, LlamaIndex, vLLM, or similar). • Solid ML Foundations: Deep algorithmic and theoretical knowledge in Machine Learning, supported by an Academic Degree (M.Sc. or Ph.D. preferred) or equivalent research experience. • Production Engineering Skills: 5+ years of software development experience, with strong, production-grade Python coding abilities and experience deploying ML systems at scale. • Self-Driven & Collaborative: An autodidact who naturally takes full ownership of problem domains, stays ahead of emerging AI trends, and thrives in a high-trust, collaborative team environment. 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.