Data Science Manager

What you will do

• Design and build predictive models to support patient analytics, including alerts, triggers, segmentation, and event prediction for specific brands or therapeutic areas.
• Lead the measurement of campaign performance and early signal analytics, including causal inference and experiment-based frameworks.
• Translate complex model outputs into clear business-facing summaries to enable decision-making by commercial and brand teams.
• Contribute to the design of pilots, A/B tests, and analytic frameworks to support test-and-learn strategy.
• Develop, validate, and maintain machine learning models using Python, PySpark, and Databricks across large longitudinal datasets.
• Maintain best practices in model versioning, QC, documentation, and reproducibility using MLflow and Git.
• Collaborate with brand partners, global analytics, and engineering teams to ensure seamless model deployment and interpretation.

Thrive | What you can expect

As we work to develop treatments that take care of others, we also work to care for our teammates professional and personal growth and well-being.

Basic Qualifications

• Masters degree in Data Science, Computer Science, Public Health, or related field.
• 5-7 years of hands-on experience in predictive modeling, machine learning, or healthcare analytics.
• Strong programming skills in Python and SQL, with experience using Databricks or similar platforms.
• Solid grasp of experimentation methods including causal inference, uplift modeling, and A/B testing.
• Experience working with patient-level or longitudinal healthcare data (e.g., claims, EMR, lab).

Preferred Qualifications

• Experience in life sciences, pharma, or regulated health analytics environments.
• Familiarity with MLflow, AWS, Git, and DevOps-style model deployment workflows.
• Understanding of patient journey analytics and use cases such as HCP segmentation or patient triggers.
• Exposure to RAG/LLM applications in data science is a plus.
• Strong communication skills and ability to work across technical and business stakeholders.