Senior Research SAS Programmer/Analyst

Mass General Brigham • Somerville, MA

5d • Hybrid

About The Position

The Senior Research Programmer/Analyst supports 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 medications and develops methods to optimize medication use. The role is part of a collaborative, multidisciplinary research environment and works with epidemiologists, biostatisticians, clinicians, and other quantitative researchers to turn scientific questions into reproducible analytic datasets and analyses.

The position focuses on developing, validating, managing, analyzing, and documenting large, complex healthcare datasets, including longitudinal insurance claims and electronic health records, as well as data from surveys and randomized trials. It emphasizes modern, efficient, reproducible programming approaches using R, Python, SQL, and related tools, while working with the Division’s established SAS-based analytic infrastructure. The role also contributes to the evolution of the Division’s programming practices and research-computing environment, mentors junior programmers/analysts, and serves as a technical resource to the team.

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 R and/or Python, including substantial experience managing and analyzing 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 in Linux/Unix command-line environments and remote computing systems.
• Experience using Git or similar version-control systems for collaborative development, code review, and reproducible research workflows.
• Ability to design modular, reusable code and analytic workflows maintainable by multiple researchers and programmers.
• 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.
• Strong proficiency in SQL and experience working with relational databases.
• Experience with SAS and the ability to understand and work with existing SAS programs and datasets.
• 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 workflows, including data cleaning, transformation, linkage, cohort construction, variable creation, and statistical analysis.
• Apply programming best practices, including quality control, code review, version control, modular and reusable programming, and clear documentation.
• Contribute to the Division’s programming and research-computing environment, particularly using R, Python, SQL, and related tools, while working with established SAS-based infrastructure.
• Identify opportunities to develop reusable tools, improve computational efficiency, and translate or integrate workflows across programming languages and platforms.
• Collaborate with faculty and research staff on ongoing and new projects.
• Participate in programmer/analyst team meetings, mentor junior programmers/analysts, and serve as a technical resource to the research team.

Benefits

• 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