Principal Data Scientist, Predictive AI

Position Overview

Genentech’s Data, Digital, and Analytics (DDA) team is dedicated to solving complex healthcare challenges and improving patient outcomes. The Principal Data Scientist serves as a visionary technical leader and strategic thought partner, driving innovation, development, and industrialization of next‑generation enterprise AI/ML applications.

Responsibilities

• Lead and guide the data science lifecycle for high‑priority AI/ML projects, serving as the subject matter expert for advanced analytical methodologies across DDA.
• Drive the end‑to‑end development, scaling, and deployment of AI solutions to optimize marketing efficiency, medical affairs strategy, and customer experience.
• Act as a critical technical advisor to leadership and cross‑functional stakeholders; influence long‑term commercial and clinical business strategies.
• Apply ML, deep learning, and applied statistics to extract high‑value insights from complex, disparate structured and unstructured data sources.
• Collaborate seamlessly with Data Science Product Owners, ML Engineers, and other teams to build production‑grade, scalable applications.
• Openly share perspectives to elevate the team’s technical maturity and optimally weigh technical vs. business trade‑offs.
• Translate complex algorithmic architectures and predictive insights into concise, compelling business narratives that inspire trust and drive immediate operational action among non‑technical stakeholders.

Qualifications

• Bachelor’s degree and 7+ years of hands‑on experience in AI with a proven track record of technical leadership and independent project execution.
• 3+ years of dedicated experience applying Recommender Systems (e.g., content‑based/collaborative filtering) and predictive/forecasting models to enterprise‑scale data to drive tangible business results.
• Deep proficiency in quantitative fields including Deep Learning (applied to recommendation engines or advanced forecasting), Causal Inference, and advanced statistical modeling.
• Strong experience working with large‑scale, complex data environments utilizing big data platforms (Hadoop, Spark) and cloud‑computing ecosystems (AWS).
• Advanced proficiency in Python and deep familiarity with open‑source machine learning and agentic libraries/frameworks (e.g., LangChain, CrewAI, TensorFlow, PyTorch).
• Preferred Master’s or PhD in Data Science, Computer Science, Applied Mathematics, Statistics or a related quantitative field.
• Deep knowledge of highly regulated environments (healthcare, pharma, biotech) with specific experience utilizing Commercial, Medical Affairs, claims, marketing, and longitudinal patient data.
• Proven ability to pivot and apply transferable AI and ML techniques across diverse business domains and ambiguous use cases.
• Experience using industry‑standard tools like Tableau, Qlik, or Data Studio to translate complex data into accessible, democratized insights.
• Strong communication, leadership, and time‑management skills, backed by a track record of open‑source contributions, peer‑reviewed publications, or patents.

Location & Work Schedule

Based in South San Francisco, CA. Hybrid schedule: 3 days per week on campus. Relocation benefits are not available for this posting.

Compensation

Expected salary range for South San Francisco, CA: $207,480 – $385,320, based on experience, qualifications, and geographic location. A discretionary annual bonus may be available based on individual and company performance.

Benefits

Genentech offers a comprehensive benefits package (link provided in the original posting). The company is an equal‑opportunity employer that prohibits unlawful discrimination and values diversity. Accommodations for applicants with disabilities are available; please contact us by completing the Accommodations for Applicants form.

Equal‑Opportunity Statement

Genentech is an equal‑opportunity employer. The company's policy prohibits unlawful discrimination, including but not limited to discrimination on the basis of protected veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.