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.
Requirements
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.
Tech Stack
Python
SQL
Benefits
A discretionary annual bonus may be available based on individual and Company performance
This position also qualifies for the benefits detailed at the link provided below.