Senior Research Programmer/Analyst Pharmacoepidemiology
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 prescription medications and to develop methods to optimize medication use. Working in a collaborative, multidisciplinary research environment, the Senior Research Programmer/Analyst will help faculty and research staff translate scientific questions into reproducible analytic datasets and analyses. 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. Advanced SAS expertise is essential because much of the Division’s established analytic infrastructure is built in SAS; R and Python are used in complementary applications and proficiency in either or both is strongly valued. The role also contributes to programming practices and research-computing tools across SAS, R, Python, SQL, and related 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 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.
- Five 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 research-team members.
Benefits
- Comprehensive benefits.
- Career advancement opportunities.
- Differentials, premiums, and bonuses as applicable.
- Recognition programs designed to celebrate contributions and support professional growth.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
