Senior Data Scientist

Position: Senior Data Scientist

Location:  San Jose CA/ Remote

Duration:  contract      

Rate: DOE

Role Overview

We are seeking highly analytical and outcome-driven Data Scientists to translate business questions into testable hypotheses, apply advanced analytical methods, and deliver evidence-based recommendations that drive measurable business impact.

Key Responsibilities

·         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.

Additional Responsibilities (Senior Data Scientist)

·         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.

Qualifications

·         Senior Data Scientist: 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.