Director of Data Science (AI)

Location: Netanya, Center District, Israel

Company

Builds responsible AI products that use market data to generate demand predictions and real-time decision intelligence for commercial teams.

What you will do

• Lead production engineering across MLOps, ML engineering, and data engineering, owning the end-to-end machine learning lifecycle from data pipelines through training, serving, and production monitoring.
• Set the roadmap with LMM management and senior executives, prioritize work across functions, and review technical trade-offs.
• Manage functional leads, hold teams accountable for delivery dates and KPIs, and own reliability, incident response, and infrastructure costs.
• Report progress and risks to senior management, product, and commercial teams, and work with applied research to move results into production.
• Hire and retain senior engineers, determine staffing, and set standards for CI/CD, automated testing, observability, and model monitoring.

Requirements

• 8+ years of engineering experience, including 5+ years leading teams and managers.
• Experience working in a multi-group environment and leading projects with inter-group dependencies.
• Production experience with time-series forecasting, reinforcement learning, or large-scale optimization.
• Experience setting the direction for a machine learning or data engineering group.
• Enough depth in production ML systems to review architecture decisions with senior engineers.
• Experience holding managers accountable for delivery dates and the metrics used to measure their teams.
• Hands-on familiarity with Python, PyTorch, Google Cloud Platform (GCP), and orchestration frameworks such as Dask and Dagster.
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a relevant field.
• Ability to explain technical decisions to commercial audiences and commercial constraints to engineers.

Nice to have

• MSc or PhD in Computer Science, Machine Learning, Statistics, Engineering, or a relevant field.
• Experience taking a machine learning platform from an early prototype to a production system used by a business.
• Experience in airlines, travel, revenue management, or dynamic pricing.
• Familiarity with real-time inference and high-volume data processing.

Culture & Benefits

• Work on AI models that set real prices in real markets.
• Collaborate with applied research, product, commercial, and senior management functions.