Senior HEOR Scientist

Roche • South San Francisco, CA

1d • $156,200 - $290,200 • Remote

About The Position

The Senior HEOR Scientist is part of Genentech’s Technical Institute team within Evidence for Access, an interdisciplinary center of excellence connecting healthcare data with health policy and market access insights. The role drives end-to-end real-world evidence (RWE) generation and observational research to inform U.S. market access and health policy strategy. Working autonomously with minimal supervision, the scientist translates business questions into rigorous study designs and scalable analytics, collaborating with health economists, policy strategists, and external health system partners.

The position leads the design, execution, interpretation, and dissemination of retrospective observational studies; analyzes complex healthcare datasets; and develops research protocols and statistical analysis plans. It applies advanced methods such as causal inference, propensity score matching, and regression modeling. The scientist also builds and maintains reusable code, libraries, and web-based applications; incorporates automation and responsible ML/AI practices; supports cross-functional initiatives; and reviews and mentors colleagues’ analytical work.

The primary location is South San Francisco, California, but the position is remote-eligible, and candidates based remotely throughout the U.S. will be considered. Relocation benefits are not approved. The expected salary range based on the primary location is $156,200–$290,200; actual pay depends on experience, qualifications, geographic location, and other permitted factors. A discretionary annual bonus may be available based on individual and company performance. The position qualifies for benefits detailed in a linked benefits resource.

Requirements

• Bachelor’s degree with 5 or more years of relevant applied analytics or economic modeling experience, or a master’s degree or PhD with 3 or more years of relevant experience in a quantitative or health-related discipline.
• Relevant disciplines include economics, epidemiology, biostatistics, data science, computer science, health services research, public policy, applied mathematics/statistics, analytics, or a related field.
• Demonstrated experience designing and conducting observational research and RWE analytics using claims, EHR, or patient registry datasets.
• Advanced proficiency developing high-quality, reproducible deliverables with programming languages and data tools such as R, Python, or SQL.
• Strong technical foundation in observational study design, advanced statistical methods, and quantitative data validation.
• Ability to work autonomously with minimal supervision, manage multiple concurrent deliverables, and maintain rigorous attention to scientific detail.
• Exceptional written and verbal communication skills, including the ability to explain technical methodologies and complex findings to non-technical stakeholders.

Nice To Haves

• Experience partnering with cross-functional stakeholders to translate strategic business needs into analytical designs and technical solutions.
• Familiarity with scalable analytics, including cloud, containers, workflow orchestration, CI/CD, or 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, such as posters, manuscripts, or methods talks, and/or contributions to internal communities of practice.

Responsibilities

• Lead the end-to-end design, execution, interpretation, and dissemination of rigorous retrospective observational studies.
• Independently analyze complex healthcare datasets, including insurance claims, electronic medical records (EMR), and patient registries.
• Develop research protocols and statistical analysis plans (SAPs).
• Select and apply advanced analytical methods, including causal inference, propensity score matching, and regression modeling.
• Design, program, and maintain efficient codebases, reusable libraries, and web-based applications using R, Python, SQL, and other relevant tools.
• Incorporate automation, workflow improvements, and responsible ML/AI methodologies to improve analytical speed, repeatability, and rigor.
• Serve as a technical subject-matter expert in internal and external strategic initiatives, aligning evidence with business and policy objectives.
• Conduct technical code reviews and quality assurance for peer analyses.
• Coach less-experienced colleagues and strengthen team capabilities.

Benefits

• A discretionary annual bonus may be available based on individual and company performance.
• The position qualifies for company benefits detailed in a linked resource.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior