HealthCare - Sr Data Scientist

• Strong Python experience, including writing code that runs in production systems. • Solid SQL skills and experience working with analytical databases (Snowflake or similar). • Hands-on experience training and tuning tree-based models (e.g., LightGBM, XGBoost, CatBoost) on real, messy data. • Experience deploying, maintaining, or owning ML models beyond experimentation (APIs, batch jobs, or streaming systems). • Comfort working across dev, staging, and production environments. • Ability to operate with limited guidance: you can ask good questions, propose solutions, and move work forward independently. • Experience at a smaller company or on a small team where you wore multiple hats. • Depth in one or more of: • Gradient boosted models and performance optimization • Feature engineering for tabular data • Data engineering / ETL design • Model monitoring, evaluation, and debugging in production • Experience improving model latency, reliability, or cost—not just accuracy. • Prior technical leadership or informal mentoring experience. • Familiarity with Airflow, Kubernetes, or cloud infrastructure. • What This Role Is Not • Not a research-only role. • Not a role where requirements are always fully specified up front. • Not a notebook-only environment. • Not a position where “training a model once” is considered done.