Senior Research Programmer/Analyst Pharmacoepidemiology

Mass General Brigham • Somerville, MA

6d • Hybrid

About The Position

The Senior Research Programmer/Analyst will support the mission of the Division of Pharmacoepidemiology and Pharmacoeconomics at Brigham and Women’s Hospital and Harvard Medical School. The Division evaluates the benefits, risks, utilization, and costs of prescription medications and develops methods to optimize medication use. The position is part of a collaborative, multidisciplinary research environment and works closely with epidemiologists, biostatisticians, clinicians, and other quantitative researchers.

The role supports research using large and complex real-world healthcare data, including longitudinal health insurance claims and electronic health records, as well as survey and randomized-trial data. The programmer/analyst translates scientific questions and study protocols into reproducible analytic datasets and analyses. Advanced SAS expertise is essential; R and/or Python proficiency is strongly valued. The position also contributes to programming practices and research-computing workflows across SAS, R, Python, SQL, and related tools.

Requirements

• Bachelor’s degree in computer science, data science, statistics, biostatistics, epidemiology, biomedical informatics, mathematics, engineering, or another relevant quantitative field.
• At least 3 years of relevant programming and data-analysis experience.
• Advanced proficiency in SAS, including substantial experience with data management and analysis of large datasets.
• Experience working with large, complex, longitudinal datasets.
• Strong programming and problem-solving skills, with careful attention to accuracy, reproducibility, and quality control.
• Ability to manage and prioritize multiple concurrent research projects.
• Experience working in Linux/Unix-based command-line environments and remote computing systems.
• Experience with version-control systems such as Git/GitHub or similar platforms.
• Ability to work effectively in multidisciplinary research teams and communicate technical concepts clearly to technical and non-technical collaborators.

Nice To Haves

• Master’s degree.
• 5 or more years of experience in a healthcare, research, or similarly data-intensive environment.
• Proficiency in R and/or Python.
• Experience with SQL and relational databases.
• Experience with healthcare claims and/or electronic health record data.
• Experience developing reusable, efficient, and reproducible data-processing or analytic workflows for large datasets.
• Familiarity with high-performance, cloud-based, or distributed computing environments and modern software development practices.
• Knowledge of epidemiologic and biostatistical methods and/or experience with emerging computational approaches, including machine learning and AI-enabled research tools.

Responsibilities

• Support faculty and research staff in developing analytic datasets and conducting statistical analyses for pharmacoepidemiologic, health services, and related research.
• Develop, validate, manage, analyze, and document large and complex healthcare datasets, including longitudinal health insurance claims and electronic health record data.
• Translate research questions and study protocols into efficient, reproducible programming workflows, including data cleaning, transformation, linkage, cohort construction, variable creation, and statistical analysis.
• Apply programming best practices, including systematic quality control, code review, version control, modular and reusable programming, and clear documentation.
• Contribute to the Division’s programming and research-computing environment across SAS, R, Python, SQL, and related tools, identifying opportunities to improve workflows, computational efficiency, and reusable infrastructure.
• Collaborate with faculty and research staff across ongoing and new research projects.
• Participate in programmer/analyst team meetings, mentor junior programmers/analysts, and serve as a technical resource to other research team members.

Benefits

• Competitive base pay.
• Comprehensive benefits.
• Career advancement opportunities.
• Differentials, premiums, and bonuses as applicable.
• Recognition programs designed to celebrate contributions and support professional growth.

What This Job Offers

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