Senior Research SAS Programmer/Analyst

Site: The Brigham and Women's Hospital, Inc. Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham. Job Summary The Division of Pharmacoepidemiology and Pharmacoeconomics at Brigham and Women’s Hospital and Harvard Medical School was created to facilitate a wide range of activities related to the use and outcomes of medications. Its mission is to bring together medicine, epidemiology, biostatistics, health services research, data science, and related disciplines to evaluate the benefits, risks, utilization, and costs of existing and new prescription medications and to develop methods to optimize medication use. The Senior Research Programmer/Analyst will support this mission as part of a highly collaborative multidisciplinary research environment comprising approximately 30 Harvard Medical School faculty members and 80 research and administrative staff, including a team of experienced research programmers/analysts. The Division’s research makes extensive use of large and complex real-world healthcare data, including longitudinal health insurance claims and electronic health records, as well as data from surveys and randomized trials. The Senior Research Programmer/Analyst will have the opportunity to work closely with epidemiologists, biostatisticians, clinicians, and other quantitative researchers to translate scientific questions into reproducible analytic datasets and analyses. The Division uses a range of programming languages and computational tools to work with large-scale, complex healthcare data. For this position, we are particularly seeking candidates with strong expertise in R, Python, and SQL who can help develop modern, efficient, and reproducible approaches to data management and analysis. A substantial body of the Division’s established analytic infrastructure is built in SAS, and familiarity with SAS – and particularly the ability to understand, work with, and translate existing SAS-based workflows – is therefore a significant advantage. This position offers an opportunity to contribute to the continued evolution of the Division’s programming practices and analytic infrastructure across languages and platforms. PRINCIPAL DUTIES AND RESPONSIBILITIES: • Support faculty and other research staff in the development of analytic datasets and the conduct of 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 and 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 to support reproducibility and collaboration. • Contribute to the development of the Division’s programming and research-computing environment, with particular emphasis on R, Python, SQL, and related tools, while working effectively with established SAS-based analytic infrastructure. • Identify opportunities to develop reusable tools, improve computational efficiency, and translate or integrate analytic workflows across programming languages and platforms. • Collaborate closely with faculty and research staff across multiple ongoing and new research projects. • Participate in programmer/analyst team meetings, mentor junior programmers/analysts, and serve as a technical resource to other members of the research team. Qualifications QUALIFICATIONS: • Bachelor’s degree in computer science, data science, statistics, biostatistics, epidemiology, biomedical informatics, mathematics, engineering, or another relevant quantitative field required. • Master’s degree preferred. • At least 3 years of relevant programming and data-analysis experience required; 5 or more years of experience in a healthcare, research, or similarly data-intensive environment preferred • Advanced proficiency in R and/or Python required, including substantial experience with data management and analysis of large datasets. • Strong proficiency in SQL and experience working with relational databases strongly preferred. • Experience with SAS strongly preferred. Because a substantial portion of the Division’s established analytic infrastructure is SAS-based, the ability to understand and work with existing SAS programs and datasets is a significant advantage. • Experience working with large, complex, longitudinal datasets required; experience with healthcare claims and/or electronic health record data strongly preferred. SKILLS/ ABILITIES/ COMPETENCIES REQUIRED: • 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 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 that can be maintained and used by multiple researchers and programmers. • Ability to work effectively in multidisciplinary research teams and communicate technical concepts clearly to both technical and non-technical collaborators. ADDITIONAL