Senior/Staff Machine Learning Data Scientist

Responsibilities

• Model Prototyping: Develop and tune innovative, new ML models and labeler systems based on deep understanding of clinical use cases and state-of-the-art ML methods.
• Productionizing: The same models that you develop with production-grade Python.
• Deploying: Identify strategies for improving our production ML-based systems, and write, debug, and deploy production-grade Python code to implement those strategies.
• Cross-Functional Alignment: Data Science for storytelling – understand model performance and metrics, and present this to technical and non-technical users, both internally and externally.

Minimum Qualifications

• Ph.D. in a relevant field plus 3+ years experience shipping ML based software products.
• Experience owning your ML models from prototyping to production, especially real-time algorithms that update dynamically across time.
• Experience writing production-grade Python and SQL code to implement and evaluate ML models in production systems.
• Track record of using statistics and performance metrics to compare end-to-end ML and product performance.

Preferred Qualifications

• Experience shipping breakthrough or 0-1 products from end to end, interpreting and leveraging State-of-the-Art methods to do so.
• Experience using messy clinical and health data to design new products for large Health Systems.
• Experience with any of the following: PyTorch, PySpark, HL7, FHIR, EHR, time series data, signal processing, MLFlow, anomaly detection, Bayesian statistics, quantile regression, time-series forecasting.