The Division uses a range of programming languages and computational tools to work with large-scale, complex healthcare data, with SAS serving as a core programming language and R and Python used in complementary applications across our research portfolio. Because a substantial body of our established analytic infrastructure is built in SAS, advanced SAS expertise is essential for this position, while proficiency in R and/or Python is strongly valued. We encourage the use of modern, efficient, and reproducible approaches to data analysis and welcome candidates who bring strong computational skills and can contribute to the continued evolution of programming practices 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 Division’s programming and research-computing environment across SAS, R, Python, SQL, and related tools, including identifying opportunities to improve workflows, computational efficiency, and reusable infrastructure.
- 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 SAS required, including substantial experience with data management and analysis of large datasets.
Proficiency in R and/or Python strongly preferred.
Experience with SQL and relational databases strongly preferred.
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 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 both technical and non-technical collaborators.
ADDITIONAL DESIRED SKILLS
The following are considered a plus but are not required
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.
Additional Job Details (if applicable)
Remote Type
Hybrid
Work Location
399 Revolution Drive
Scheduled Weekly Hours
40
Employee Type
Regular
Work Shift
Day (United States of America)
Pay Range
$79,560.00 - $115,720.80/Annual
At Mass General Brigham, we believe in recognizing and rewarding the unique value each team member brings to our organization. Our approach to determining base pay is comprehensive, and any offer extended will take into account your skills, relevant experience if applicable, education, certifications and other essential factors. The base pay information provided offers an estimate based on the minimum job qualifications; however, it does not encompass all elements contributing to your total compensation package. In addition to competitive base pay, we offer comprehensive benefits, career advancement opportunities, differentials, premiums and bonuses as applicable and recognition programs designed to celebrate your contributions and support your professional growth. We invite you to apply, and our Talent Acquisition team will provide an overview of your potential compensation and benefits package.
EEO Statement
2200 The Brigham and Women's Hospital, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, national origin, sex, age, gender identity, disability, sexual orientation, military service, genetic information, and/or other status protected under law. We will ensure that all individuals with a disability are provided a reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. To ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Veteran’s Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact Human Resources at (857)-282-7642.
Mass General Brigham Competency Framework
At Mass General Brigham, our competency framework defines what effective leadership “looks like” by specifying which behaviors are most critical for successful performance at each job level. The framework is comprised of ten competencies (half People-Focused, half Performance-Focused) and are defined by observable and measurable skills and behaviors that contribute to workplace effectiveness and career success. These competencies are used to evaluate performance, make hiring decisions, identify development needs, mobilize employees across our system, and establish a strong talent pipeline.
