Senior Data Scientist — Berlin – Health Technology

Senior Data Scientist — Berlin – Health Technology

We are working with a Berlin based AI-native patient intelligence company, backed by leading European healthtech investors. Their platform captures something the life sciences industry has never been able to access at scale: the patient's own account of living with a chronic or rare condition.

About the role

This role puts you at the heart of how that data becomes intelligence.

Working closely with their Chief AI Officer, you'll take unstructured patient narratives, hundreds of data points per person, and turn them into the models, metrics, and evidence that our clients act on. The questions are genuinely open: how do you quantify a patient journey? What signals predict a treatment switch? Where does the data reveal unmet need no one has named yet?

It's a role with unusually short distance between analysis and impact. What you build ships into a live product, in front of global life science teams, and shapes decisions that reach patients with chronic conditions worldwide.

What you'll do

• Analyze and model large, multi-modal patient datasets to surface insights on patient journeys and unmet needs
• Partner with the Chief AI Officer to develop, validate, and scale the algorithms behind our Patient Journey Analytics Platform
• Work with engineers and product managers to turn data insights into user-facing features
• Design and implement pipelines for data cleaning, feature engineering, and predictive modeling
• Communicate results clearly to technical and non-technical audiences, shaping how life science companies make decisions
• Keep pace with state-of-the-art ML/AI methods and bring new ideas into our production stack

What you'll bring

• 3+ years' professional experience as a Data Scientist, ideally in healthtech, SaaS, or a related field
• Strong Python (pandas, scikit-learn, PyTorch/TensorFlow or similar)
• Strong SQL and experience with both structured and unstructured data
• Solid grounding in statistical modeling, machine learning, and data visualization
• Familiarity with cloud environments (AWS, GCP, or Azure)
• Ability to run independently on complex problems while collaborating closely with product and engineering
• Full professional fluency in English, written and spoken