Senior Principal Data Scientist (Healthcare & Life Sciences)

Job Title: Senior Principal Data Scientist (Healthcare & Life Sciences)

Job Location: South San Francisco, CA - Hybrid

Job Duration: Long Term

Position Overview

As a Senior Principal Data Scientist, you will serve as a technical visionary and strategic partner within the Product Development Data Sciences organization. You will lead the design and implementation of advanced analytical solutions that transform complex biological, clinical, and real-world data (RWD) into actionable insights. Your work will directly impact clinical trial design, regulatory submissions, and the delivery of personalized healthcare solutions.

Key Responsibilities

• Strategic Leadership: Act as a thought leader in defining the roadmap for data science capabilities. Partner with clinical, medical, and commercial leaders to translate high-level scientific questions into robust analytical frameworks.
• Advanced Modeling & AI: Lead the development of predictive models using machine learning (ML), deep learning, and causal inference to optimize patient recruitment, identify novel biomarkers, and simulate clinical trial outcomes.
• Data Ecosystem Architecture: Oversee the integration and productization of diverse data streams, including EHR, Claims, Genomics, and Digital Health data, ensuring alignment with FAIR (Findable, Accessible, Interoperable, Reusable) principles.
• Regulatory & Quality Excellence: Guide teams in navigating the regulatory landscape (e.g., FDA/EMA) for AI/ML-based evidence. Ensure all analytical workflows comply with Google Cloud Platform, HIPAA, and GDPR standards.
• Mentorship & Influence: Technical lead for a global team of data scientists and engineers. Foster a culture of technical excellence, reproducibility, and continuous learning through code reviews and architectural audits.

Education

• PhD (strongly preferred) or Master’s in Data Science, Bioinformatics, Statistics, Computer Science, or a related quantitative field.

Experience

• 12+ years of professional experience in data science, with at least 8 years specifically within the Biotech, Pharma, or Healthcare sectors.

Technical Stack

• Expert proficiency in Python or R; Deep experience with SQL, Spark, and cloud-native environments (AWS/Google Cloud Platform/Azure).

Domain Knowledge

• Deep understanding of the drug development lifecycle, clinical trial data standards (CDISC/SDTM/ADaM), and healthcare ontologies (OMOP, FHIR, ICD-10).
• Mastery of longitudinal data analysis, survival analysis, Bayesian statistics, and high-dimensional data visualization.

 Education & Experience

• Bachelor's degree in Information Technology, or a related field.