Research Analyst

We are seeking a highly motivated Research Analyst to support computational and statistical research focused on type 2 diabetes, precision prevention, and large-scale multi-omics data integration. The successful candidate will play a key role in developing, implementing, and maintaining reproducible analytical pipelines for large biomedical datasets, including genomics, metabolomics, proteomics, clinical, and epidemiologic data.

This position is ideal for a candidate with strong quantitative and programming skills who is interested in applying computational approaches to understand the molecular and environmental determinants of type 2 diabetes and related metabolic traits.

• Master's degree in computational biology, bioinformatics, biostatistics, statistics, epidemiology, computer science, data science, or a related quantitative field.
• Experience managing or analyzing large-scale omics datasets, including metabolomics, proteomics, genomics, transcriptomics, or other high-dimensional molecular data.
• Strong programming skills in R and/or Python.
• Familiarity with version control systems, such as Git or Git Hub.
• Strong organizational skills and attention to detail.
• Ability to work independently while also collaborating effectively with a multidisciplinary research team.
• Strong written and verbal communication skills.
• Interest in type 2 diabetes, cardiometabolic disease, precision prevention, health disparities, and/or multi-omics research.

The ideal candidate will be highly organized, detail-oriented, and motivated to develop robust computational infrastructure for biomedical research. They should be comfortable working with complex datasets, troubleshooting analytic workflows, documenting code and results, and contributing to a collaborative research environment. This role requires both technical expertise and scientific curiosity, with an emphasis on reproducibility, transparency, and rigorous data management.

The Senior Analyst will join a collaborative and interdisciplinary research environment focused on integrating molecular, genetic, clinical, behavioral, and environmental data to improve type 2 diabetes prevention. The role will provide opportunities to contribute to publications, presentations, grant proposals, and the development of analytic resources that support multiple ongoing projects in the lab.