Senior Data Scientist

We are seeking a Senior Data Scientist to join the team that builds the predictive intelligence powering the app. You will own the ML models behind user engagement, cardiovascular risk stratification, and personalized health recommendations - the systems that determine what users see, when they're nudged, and how their health trajectories are shaped.

This role demands both statistical depth and engineering proficiency - you will be expected to take models from research through to deployment, write code built for production, and use AI coding assistants fluently as part of how you get work done.

Responsibilities
Lead end-to-end development of predictive ML models. From data exploration and feature engineering through training, validation, deployment, and ongoing monitoring across engagement and clinical risk domains.
Apply strong statistical foundations to model design, feature selection, uncertainty quantification, and interpretation of results
Write production-grade Python code tha

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Qualifications:
5+ years of hands-on experience developing, deploying, and maintaining ML models in production environments.
Bachelor's degree in Statistics, Computer Science, Applied Mathematics, Engineering, or a related quantitative field - a strong statistical foundation is essential for this role.
Deep expertise in statistics and probability: distributions, inference, hypothesis testing, Bayesian methods, causal inference, and experimental design, with the ability to apply these rigorously in a healthcare context.
Strong software engineering skills in Python: production-grade practices, version control, testing, and reproducibility.
Proficiency using AI coding assistants as a core part of the development workflow.
Expertise with ML frameworks such as PyTorch, scikit-learn, XGBoost, or LightGBM.
Experience building or working within ML pipelines end-to-end, including feature engineering, model registries, and deployment tooling.
Strong ability to translate complex statistical and