Sr Data Scientist

Role Description

• Translate approved business questions into testable hypotheses sized at one to three days with clear exit criteria and confidence levels.
• Design and execute analytical methods including segmentation, causal inference, forecasting, propensity modeling, uplift modeling, and experiment design.
• Defend analytical methodology and findings during review and governance forums.
• Provide an initial evidence-based answer within five business days, including inconclusive or negative results.
• Maintain daily progress updates covering hypotheses tested, findings, confidence level, next steps, and blockers.
• Develop production-quality, version-controlled analytical code with reproducible notebooks and documented assumptions.
• Partner with Data Engineers to define features, granularity, historical data requirements, and address data gaps proactively.
• Convert validated findings into metric definitions and business logic for visualization and reporting.
• Collaborate with client data scientists and provide comprehensive model documentation for handover and reuse.

Qualifications

• 10+ years of applied data science experience.
• Advanced proficiency in Python and/or R and SQL.
• Demonstrated experience deploying analytical models into production.
• Strong foundation in statistics, machine learning, experimentation, and predictive analytics.
• Strong background in statistics, mathematics and with data science degree.
• Healthcare, medical device, life sciences, or regulated-industry experience preferred.

Requirements

• Serve as analytics lead for the pod.
• Own analytical quality across engagements.
• Act as peer reviewer and mentor internal and client analysts.
• Drive analytics best practices and technical excellence.