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Neko Health is seeking a Data Science Pod Lead to join its Data Science team in Stockholm. This is a dual-track role combining deep hands-on technical expertise with people leadership. 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 25% will be dedicated to people leadership as the direct line manager and mentor for a pod of data scientists.
You will work across projects including Laser Speckle Imaging, contactless ECG, skin imaging, thermal imaging, cardiovascular algorithms, and tissue imaging—turning complex health data into validated, clinically impactful decision support systems. You will shape the technical direction and quality standards of your pod, contribute to broader Data Science leadership strategy, and collaborate closely with engineers, clinicians, and researchers to bring algorithms from prototype to production.
In your first 6–12 months, you will develop, verify, validate, and deploy machine learning models for clinical decision support; build and lead a high-performing pod of data scientists with line management and mentorship responsibilities; set and uphold technical standards and code quality within the pod; collaborate cross-functionally with hardware engineers, firmware engineers, software engineers, medical doctors, and clinical researchers; and contribute to Data Science leadership team strategy and best practices.
Required qualifications include an MSc or PhD in Machine Learning, Computer Science, Physics, Biomedical Engineering, or related quantitative field; 5+ years of industry experience as a Data Scientist, ML Engineer, or Applied Scientist (or 2+ years post-PhD); demonstrated track record of shipping algorithms or ML models to production in real-world product or clinical environments; deep expertise in machine learning, signal processing, or computer vision with hands-on full ML lifecycle experience; strong software engineering skills including production-level coding, version control, testing, and backend integration; experience with sensor data, time-series analysis, or medical imaging in cross-functional R&D environments; people leadership experience with ability to inspire and develop technical teams; and strong communication and collaboration skills.
Preferred qualifications include experience in regulated environments (medical devices, IVD), prior AI-enabled healthcare or medtech experience, systems thinking for end-to-end ML systems design, and demonstrated mentoring success in high-growth mission-driven organizations.
