Top Data Science Jobs in Israel

Build and productionize applied machine learning models using game, player, and operational data. Responsibilities include problem formulation, data preparation, feature engineering, model evaluation, forecasting, classification, segmentation, anomaly detection, deployment, monitoring, and documentation. The role partners with product and business teams to connect model performance to outcomes and applies LLM and agent capabilities where useful.

Leads data science for monday.com’s agentic product while directing a cross-R&D guild of approximately 10 data scientists. Responsibilities include building production agent evaluation systems, analyzing traces, improving model and tool-use quality, setting data science standards, mentoring and managing talent, hiring, and advising leaders on AI strategy and product decisions.

Lead strategy, roadmap, and execution for AI security attack and defense engines. Own adversarial testing, guardrails, evaluation metrics, benchmark datasets, data strategy, and the transition from research to production. Partner with data science, engineering, security, design, sales, and enterprise customers to define measurable quality standards, prioritize model capabilities, and translate customer risks into product requirements.

Conduct research on AI security agent behavior by forming hypotheses, designing experiments, analyzing traces and failure modes, and building research harnesses. Develop AI projects from proof of concept through production, including algorithms, pipelines, memory, context, and evaluation systems. Monitor emerging models and research, publish findings, and present at industry conferences while supporting customer-facing AI infrastructure.

Lead the vision, strategy, roadmap, and execution for Similarweb’s Sales Intelligence product. Manage product managers and collaborate with engineering, design, data science, sales, marketing, operations, and research teams. Conduct customer and market research, prioritize and design features, launch beta programs, monitor KPIs, analyze user behavior, and iterate products. The role also requires hands-on AI product delivery and development of agentic workflows.

Own intent-drift detection for AI coding agents, including dataset design, labeling, feature and representation development, model training, distillation, quantization, architecture decisions, and evaluation. Build small, low-latency models that run locally on developer machines with very low false-positive rates. The role requires end-to-end applied data science experience, small-model fluency, an applied research mindset, independence, and startup adaptability, with security and adversarial machine learning experience preferred.

Lead data scientists and data engineers developing scalable data platforms, distributed batch and streaming pipelines, and machine learning products for price optimization. Own data architecture, quality, testing, observability, and deployment practices while contributing hands-on to technical decisions. Manage sprint planning, code reviews, recruitment, mentorship, and performance feedback. Research pricing models and algorithms and ensure reliable, high-performance decision systems.

Leads Cynet’s Product, Engineering, and Counter Adversary Operations organizations, owning company-wide technology and product strategy, AI adoption, product quality, release predictability, cybersecurity platform integration, and customer outcomes. Serves as Managing Director of the Tel Aviv office, overseeing site stability, culture, talent attraction, employee experience, and cross-team leadership. Partners with executive leadership to align technology and product strategy with commercial goals.

Lead the Payment Fraud product roadmap to maximize approvals and minimize fraud by partnering with engineering, data science, analysts, and sales. Drive new market entry through vertical research, merchant engagement, pilot programs, and performance tracking (approval rates, fraud rates, chargeback impact).

Manage strategic enterprise client relationships across multiple verticals, serving as the primary contact and ensuring satisfaction, commercial performance, product adoption, renewals, and successful delivery. Translate client goals into actionable plans, coordinate cross-functional teams, monitor performance metrics, identify expansion opportunities, and represent customer needs internally. Requires frequent travel to Genoa, Italy, approximately twice monthly.

Leads the global Data Science function, setting strategy and managing teams while driving machine learning, optimization, forecasting, and statistical modeling solutions. Partners with Product, Engineering, Customer Success, and executives to translate business challenges into scalable analytical products, establish experimentation and model evaluation practices, support customer engagements, and shape the company’s AI roadmap.

Lead the production engineering organization responsible for the market model’s data pipelines, ML training and serving, infrastructure, monitoring, reliability, and costs. Set roadmaps and priorities across MLOps, ML engineering, and data engineering; manage functional leads; oversee delivery, KPIs, hiring, technical standards, and cross-functional collaboration. Partner with applied research to productionize models and communicate progress, risks, and technical decisions to executives, product, commercial teams, and engineers.

Leads production engineering for an AI market model, overseeing MLOps, machine learning engineering, data engineering, infrastructure, data pipelines, model training and serving, monitoring, reliability, costs, KPIs, and delivery. Manages functional leads, sets technical roadmaps and standards, partners with applied research and commercial teams, hires senior engineers, and ensures machine learning systems operate reliably in customer-facing production environments.

Own and scale a core growth domain within the Car product: define strategy and roadmap, ship and optimize features, and partner with engineers, data scientists, actuaries, designers, marketers, and analytics to drive acquisition, activation, engagement, monetization, and AI-native experiences for autonomous-car insurance.

Own the freelancer experience at Fiverr, leading a cross-functional team to improve matching quality, develop roadmaps, and drive product innovation for freelancers.

Lead and grow a multidisciplinary Data Science engineering team building real-time content moderation, GenAI safety and red-teaming systems, and Databricks-based data and MLOps platforms. Set technical direction, own delivery and quality, mentor and hire engineers, review designs, and drive reliability, observability, CI/CD, cost, latency, and production ML excellence across Python, Rust, Spark, AWS, Kubernetes, and model-serving infrastructure.

Lead end-to-end research to produce production-ready predictive signals for underwriting, risk, environmental/catastrophe, and behavioral models. Design methods from first principles, evaluate and validate models, investigate production model behavior, and deploy monitored, reproducible solutions with clear documentation.