Principal Data Scientist

• Collaborate with E4A HEOR and health policy project owners to identify the appropriate in-house databases (e.g., claims/survey/electronic medical record) and design appropriate methodology to answer specific research questions and to address business needs.
• Participate in E4A strategic planning and lead the execution of in-house RWD studies of E4A HEOR and health policy project owners.
• Develop and/or oversee research protocol and statistical analysis plan. Recommend and implement appropriate analytical methodology (e.g., propensity score matching, regression analysis...etc) for RWD studies.
• Mentor junior TI members to conduct the analyses, to review the results, and to communicate/publish findings. Lead and oversee the analytic execution to ensure the analyses are conducted with the highest accuracy and quality.
• Develop knowledge in the covered disease area and identify new data source, method, and collaboration opportunities to address business needs.
• Assist internal stakeholders to review protocol and to support the design of external observational research.
• Establish a strong partnership with E4A and other stakeholders to ensure high impact from the in-house collaboration.
• Prioritize resource and support based on the business impact of deliverables.
• When assigned, represent E4A in internal and/or external cross-functional, strategic planning and/or other programs on innovative methodology or technology.
• Support the Head of E4A TI on operational excellence. Assist with recruitment, ongoing coaching/mentoring, and training of junior staff.
• Participate in all required Genentech and E4A training and development programs. Comply with all internal policies and external regulations.

The Principal Data Scientist of the Technical Institute (TI) is a member of the Evidence for Access (E4A) unit in the US Public Affairs and Access department. He/she serves as the TI point of contact for E4A health economics outcomes research (HEOR) members to design and execute observational research using in-house real-world data (RWD). This role involves hands-on coding in analytics software. Economic modelling experience is a plus., * You have a Master's Degree (health policy and management, economics, epidemiology, public policy, or health services research);

• You have at least 6 years for Master's degree of prior work experience in academic/research institute, consulting, managed care, government, and/or pharmaceutical industry.
• Deep expertise in observational research methodology. Ability to recommend data sources and to design analyses that answer research questions.
• Strong oral and writing communication skills to summarize and explain the findings to audiences who may not have technical background.
• Strong hands-on research and programming (R, Python is a plus) experience of large claims databases and/or electronic health records data.
• SQL and macro programming experience
• Excellent knowledge in the US reimbursement coding system.
• A strong track record of publication in peer-reviewed journals.
• Experience in partnering with cross-functional stakeholders
• Strong attention-to-detail.
• Ability to work collaboratively in a dynamic, team-based environment
• Ability to prioritize and adjust project plans appropriately
• Demonstrated ability to learn and embrace new technologies, applications and solutions
• Ability to mentor intern, fellow, and/or junior staff.

Preferred Qualifications

• Doctoral Degree in above or other related disciplines.
• A minimum of four years for Doctoral Degree candidates of prior work experience in academic/research institute, consulting, managed care, government, and/or pharmaceutical industry

This role is South San Francisco, CA preferred however may consider remote options