Data Science Pod Lead

We are looking for a Data Science Pod Lead to join our Data Science team — a senior technical leader who combines deep hands-on expertise with a passion for growing people and teams. Approximately 75% of your time will be spent as an individual contributor, developing and delivering production-ready algorithms and ML models from novel sensor data, while approximately 25% will be dedicated to people leadership, serving as the direct line manager and mentor for a pod of data scientists.

What you'll do

• Develop, verify, validate, and deploy machine learning models and algorithms for clinical decision support, contributing to new product features or research breakthroughs that improve member outcomes.
• Build and lead a high-performing pod of data scientists — providing line management, mentorship, regular feedback, and career development support to help each team member thrive.
• Set and uphold technical standards, code quality, and best practices within the pod, and deliver production-quality code integrated into Neko's backend infrastructure.
• Collaborate cross-functionally with hardware engineers, firmware engineers, software engineers, medical doctors, and clinical researchers to develop and validate clinical use-cases, and support the regulatory readiness of algorithms and models.
• Contribute to the Data Science leadership team — shaping area-wide strategy, best practices, common tooling, and ways of working alongside other Pod Leads and the Area Lead.

What you'll need

• MSc or PhD in Machine Learning, Computer Science, Physics, Biomedical Engineering, or a related quantitative field.
• 5+ years of relevant industry experience in a Data Scientist, ML Engineer, or Applied Scientist role, or 2+ years post-PhD in a comparable position.
• Demonstrated track record of shipping algorithms or ML models to production in a real-world product or clinical environment.
• Deep expertise in machine learning, signal processing, or computer vision, with hands-on experience across the full ML lifecycle.
• Strong software engineering skills: production-level coding, version control, testing, and integration with backend systems.
• Experience working with sensor data, time-series analysis, or medical imaging in cross-functional R&D environments.
• People leadership experience (e.g. line management, team lead, or equivalent), with the ability to inspire and develop a technical team.
• Strong communication and collaboration skills, with comfort operating under uncertainty, making pragmatic trade-offs, and driving clarity in ambiguous situations.

Nice to have

• Experience working in a regulated environment (e.g. medical devices, IVD, or equivalent) and familiarity with regulatory requirements for medical algorithms.
• Prior experience in AI-enabled healthcare, medtech, or biotech.
• Systems thinking: ability to design and reason about end-to-end ML systems that are observable, safe, and scalable.
• Demonstrated success mentoring engineers or researchers in high-growth, mission-driven organisations.