Statistical Analyst​/Research Programmer

Overview

Company Description By working at Harvard University, you join a vibrant community that advances Harvard's world-changing mission in meaningful ways, inspires innovation and collaboration, and builds skills and expertise. We are dedicated to creating a diverse and welcoming environment where everyone can thrive.

Why join the Harvard T.H. Chan School of Public Health? The Harvard T.H. Chan School of Public Health is a world-renowned institution dedicated to advancing public health through cutting-edge research, education, and global collaboration. Our school is a special place to work because of its vibrant, mission-driven community, interdisciplinary approach, and commitment to addressing some of the most pressing health challenges worldwide.

We foster a collaborative and inclusive work environment where innovation, continuous learning, and work-life balance are valued.

Learn more about the School’s mission, objectives, and core values, our Principles of Citizenship, and about the Dean’s AAA vision about our school’s ongoing strategic initiatives.

The Department of Health Policy and Management (HPM) at the Harvard T.H. Chan School of Public Health seeks a highly motivated Statistical Analyst / Research Programmer to support a portfolio of multidisciplinary health policy and health services research projects. This position is embedded in an academic research environment and is focused on the analysis of large-scale Medicare and Medicaid administrative claims and assessment data, often exceeding one million beneficiaries across multiple years.

The successful candidate will work closely with faculty investigators, statisticians, and research staff to prepare, manage, and analyze complex health care data to inform peer-reviewed publications, policy briefs, and funded research initiatives. This role is well suited for individuals with strong quantitative and statistical programming skills who are interested in applied health policy research rather than software or product development.

Project topics include, but are not limited to:

• Evaluating the impact of Medicaid Managed Care adoption on medical care utilization, long-term services and supports (LTSS), and beneficiary outcomes
• Identifying populations likely eligible for exemptions to Medicaid work requirements using claims and eligibility data
• Assessing the effects of the COVID-19 public health emergency on medical and LTSS outcomes, including variation by state policy responses
• Examining the role of Medicaid Home and Community-Based Services expansions on Medicare and Medicaid costs and quality outcomes
• Developing predictive analytic models to identify individuals with disabilities and older adults likely to use LTSS or transition across care settings
• Developing and implementing analytic approaches to measure health disparities experienced by people with disabilities across the health care system

This position is ideal for candidates seeking hands-on experience in health services and health policy research prior to pursuing advanced graduate training (e.g., PhD, DrPH, MD). A core component of the HPM mission is to train the next generation of health policy and health system leaders, and faculty are committed to providing mentorship and professional development aligned with the successful candidate’s long-term goals.

Learn more about the Department of Health Policy and Management here: https://(Use the "Apply for this Job" box below)./

The Statistical Analyst/Research Programmer will collaborate with faculty and research team members on a range of analytic and data management tasks, including but not limited to:

• Managing, organizing, and documenting large, longitudinal Medicare and Medicaid claims and assessment datasets, often spanning multiple years and data sources
• Designing and maintaining analytic datasets, including complex data linkage, merging, and transformation workflows
• Conducting statistical analyses using STATA as the primary analytic tool, with SAS and/or R used as complementary tools when appropriate
• Working with restricted-access federal data sources, including CMS Virtual Research Data…