Senior Research SAS Programmer/Analyst
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 brings together medicine, epidemiology, biostatistics, health services research, data science, and related disciplines to evaluate the benefits, risks, utilization, and costs of medications and develop methods to optimize medication use. The role is part of a collaborative multidisciplinary research environment with approximately 30 Harvard Medical School faculty members and 80 research and administrative staff, including experienced research programmers and analysts. The Division works with large, complex real-world healthcare data, including longitudinal health insurance claims and electronic health records, as well as survey and randomized-trial data. The position works closely with epidemiologists, biostatisticians, clinicians, and other quantitative researchers to turn scientific questions into reproducible analytic datasets and analyses. The position emphasizes R, Python, and SQL to develop modern, efficient, and reproducible approaches to data management and analysis. Because much of the Division’s established analytic infrastructure is built in SAS, the ability to understand, work with, and translate existing SAS workflows is a significant advantage. The role also contributes to the continuing evolution of the Division’s programming practices and analytic infrastructure across languages and platforms.
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.
- Five 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, particularly 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 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, particularly using R, Python, SQL, and related tools, while working 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 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 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.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
