Senior Data Scientist/Computational Biologist

Harvard University • Boston, MA

37d • Hybrid

About The Position

The Core for Computational Biomedicine (CCB) in the Department of Biomedical Informatics (DBMI) at Harvard Medical School (HMS) is looking for an experienced Senior Data Scientist/Computational Biologist to advance in CCB’s mission to leverage data and computation to transform research and improve health. CCB provides computational and analytic resources to advance scientific discovery within HMS through its multi-disciplinary team of computational and quantitative scientists who work on collaborative projects both within the center and with members of the HMS community. The role will involve processing, analyzing, and integrating public and newly generated single-cell and spatial multi-omics datasets in collaboration with experimental labs at HMS. This will include developing sustainable tools, software packages, and integrated data science products that empower research labs to explore, analyze, and interpret their data. The data sources will often be at the leading edge of scientific discovery and will therefore require methodological work, algorithm development, and technical developments. The ideal candidate will be proficient in R and/or Python, have strong quantitative, analytical, and communication skills, and will be able to work independently and collaboratively on scientific problems and deliver solutions. There will be opportunities for working in teams and independent decision making at all levels of bioinformatic processing and statistical analysis of the data, as well as examining, evaluating, and recommending analytical approaches to collaborating labs. In addition, methodological developments for novel and challenging data analysis and integration tasks arise frequently requiring originality and creativity, including designing and analyzing follow-up experiments.

Requirements

• Minimum of seven years’ post-secondary education or relevant work experience.
• PhD in Bioinformatics, Biostatistics, Computer Science, Statistics or related field- strongly preferred.
• Substantial experience in analyzing genetic, genomic, or image data.
• Ability to program at a high level in R or Python.
• Ability to work independently.
• Experience with analyzing single-cell and spatial omics data.
• Working knowledge of git or similar tools for scientific software development.
• Experience writing data publishing tools that support user interaction such as RStudio's Shiny or Connect applications.
• Experience with machine learning frameworks such as TensorFlow or PyTorch.
• Ability to work on teams.
• Strong communication skills.

Nice To Haves

• Completion of Harvard IT Academy specified foundational courses (or external equivalent) preferred.

Responsibilities

• Faculty-facing analytics and computational biology support
• Lead integrative data analyses for HMS research groups, with emphasis on single-cell and multi-omic datasets. Execute projects with clearly defined scope independently and in partnership with HMS faculty collaborators, provide technical guidance, and communicate results in a clear, actionable manner.
• Development and maintenance of scalable, reproducible pipelines
• Design, implement, document, and maintain robust analysis workflows (e.g., QC, integration, statistical modeling, reporting) to support repeatable, high-quality computational research across multiple projects.
• AI-enabled methods and applied research tooling
• Evaluate and implement AI-assisted approaches that accelerate research workflows (e.g., knowledge extraction, annotation support, literature review and writing workflows) while ensuring scientific rigor, reproducibility, and responsible use.
• Training, workshops, and internal enablement
• Develop and deliver hands-on workshops and learning materials for HMS researchers; provide office hours and consultation to promote best practices in computational biology, reproducible research, and AI-enabled workflows.
• Open-source software and biomedical data asset development
• Contribute to and maintain open-source software and data resources (including distribution through established ecosystems such as Bioconductor and PyPI), support releases and user documentation, and engage with external developer communities to increase adoption and impact.

Benefits

• Generous paid time off including parental leave
• Medical, dental, and vision health insurance coverage starting on day one
• Retirement plans with university contributions
• Wellbeing and mental health resources
• Support for families and caregivers
• Professional development opportunities including tuition assistance and reimbursement
• Commuter benefits, discounts and campus perks

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree