Senior HEOR Scientist

This role is a vital part of our Technical Institute (TI) team within Evidence for Access (E4A), which serves as an interdisciplinary center of excellence bridging raw healthcare data with actionable health policy and market access insights. As a member of this pioneering team, you will have the opportunity to collaborate closely with cross-functional partners, including Health Economists, policy strategists, and external health system partners, to deliver end-to-end evidence generation. Through real-world evidence and modern analytics, you will directly shape the future of healthcare delivery, advance patient access, and improve population health.

The Opportunity

As a Senior HEOR Scientist, you will drive end-to-end Real-World Evidence (RWE) generation and observational research to directly shape US market access and health policy strategy. Working autonomously with minimal supervision, you will translate complex business questions into rigorous study designs and scalable analytics that deliver decision-ready insights. Key responsibilities include:

• Lead End-to-End Evidence Generation: Oversee the end-to-end design, execution, interpretation, and dissemination of rigorous retrospective observational studies.
• Execute Secondary Data Analytics: Independently analyze complex healthcare datasets—including insurance claims, electronic medical records (EMR), and patient registries—while formulating robust research protocols and statistical analysis plans (SAPs).
• Champion Methodological Rigor: Select and apply advanced analytical frameworks, such as causal inference, propensity score matching, and regression modeling, to solve critical business problems.
• Build Scalable Tools & Infrastructure: Design, program, and maintain efficient codebases, reusable libraries, and web-based applications (using R, Python, SQL, and other relevant tools) to standardize and accelerate evidence generation.
• Modernize Analytics & AI Practices: Incorporate automation, workflow enhancements, and responsible ML/AI methodologies to improve analytical speed, repeatability, and rigor.
• Drive Cross-Functional Collaboration: Serve as a technical subject-matter expert within internal and external strategic initiatives, aligning data-driven evidence with broader business and policy objectives.
• Foster Peer Mentorship & Quality: Provide technical code reviews and quality assurance for peer analyses while coaching less-experienced colleagues to strengthen overall team capabilities.

While the primary location for this role is South San Francisco, CA, this is a full-time remote-eligible position. Candidates based remotely throughout the U.S. will be fully considered.

Who You Are

• Education & Experience: Bachelor’s degree with 5+ years of relevant applied analytics/economic modeling experience, or a Master’s degree or PhD with 3+ years of relevant experience in a quantitative or health-related discipline (e.g., economics, epidemiology, biostatistics, data science, computer science, health services research, public policy, applied math/statistics, analytics, or related).
• RWE & Healthcare Data Expertise: Demonstrated track record designing and conducting observational research and RWE analytics utilizing claims, EHR, or patient registry datasets.
• Technical Programming Proficiency: Advanced proficiency in developing high-quality, reproducible deliverables using programming languages and data tools such as R, Python, or SQL.
• Methodological & Analytical Acumen: Strong technical foundation in observational study design, advanced statistical methods, and quantitative data validation.
• Independent Execution & Problem-Solving: Proven ability to work autonomously with minimal supervision, manage multiple concurrent deliverables, and demonstrate rigorous attention to scientific detail.
• Cross-Functional Communication: Exceptional written and verbal communication skills, with the demonstrated ability to translate technical methodologies and complex findings to non-technical stakeholders.

Preferred Experience:

• Experience partnering with cross-functional stakeholders to translate strategic business needs into actionable analytical designs and technical solutions.
• Familiarity with scalable analytics (cloud, containers, workflow orchestration, CI/CD, QA automation), and/or responsible ML/AI use.
• Exposure to economic modeling in Excel (and/or VBA) or R, including structured documentation and sensitivity analysis approaches.
• Publication or external communication experience (posters, manuscripts, methods talks) and/or contributions to internal communities of practice.
  

The expected salary range for this position based on the primary location of South San Francisco CA is $156,200 - $290,200. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed in this link.

Relocation benefits are not approved for this posting.

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Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. 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.

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