About the role

We're looking for a hands-on Data Science Team Lead to lead a team of Data Scientists developing advanced AI solutions for digital pathology, oncology, and drug development.

This role combines deep technical ownership with people leadership. You will lead the team's research and model development, define technical approaches, drive execution, and remain closely involved in solving the most challenging machine-learning and computer vision problems.

This role is perfect for you if you enjoy working with multimodal biomedical data, deep learning, computer vision, and LLM-based workflows, and collaborating closely with Engineering, Product, Pathology, and Scientific teams.

Responsibilities

• Lead, mentor, and develop a team of Data Scientists.
• Own technical direction, priorities, execution, and delivery.
• Break complex ML, computer vision, and research problems into clear, executable projects.
• Provide hands-on leadership across model development, experimentation, and evaluation.
• Maintain a high technical standard through model, experiment, and code reviews.
• Drive adoption of state-of-the-art AI methods, tools, and development workflows.

Requirements

• M.Sc. in Computer Science, Software Engineering, Data Science, or a related field.
• 6+ years of hands-on ML/deep-learning experience, including 2+ years leading an ML/Data Science team.
• Proven experience bringing ML developments into production with strong practices around experiment management, dataset/model versioning, reproducibility, traceability, testing, and cross-functional handoff to software and product teams.
• Strong hands-on expertise in deep learning and computer vision, including image segmentation, model architecture, training, optimization, and debugging.
• Proven ability to take complex ML projects from ambiguous research questions to robust, reproducible solutions.
• Deep practical experience with coding agents such as Cursor, Claude Code, or Codex, including rules/instructions, skills, tools, MCP, and automated development workflows.
• Strong understanding of model evaluation, experimental design, and building reliable AI systems.

Additional information:

• Location: Tel Aviv (close to train and light rail)
• Work model: 4 days per week in the Tel Aviv office + 1 fixed work-from-home day (Tuesdays)
• Employment type: Full-time, global contract