Data Scientist/Computational Biologist

Harvarduniversity; Boston (MA); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Harvard University seeks an experienced Data Scientist/Computational Biologist to advance a data-driven research program in the Core for Computational Biomedicine at HMS. The role focuses on processing and integrating single-cell and spatial omics data, developing tools, and building data science products for HMS labs.

The ideal candidate has a PhD in a relevant field, strong R/Python skills, and a track record in computational biology, machine learning, and open-source software development.

Qualifications

• Strong background in bioinformatics or computational biology.
• Experience with single-cell and spatial omics data analysis.
• Proficiency in R and/or Python for data analysis and visualization.

Responsibilities

• Develop scalable, reproducible analysis pipelines.
• Collaborate to design and implement analysis workflows (QC, integration, modeling, reporting).
• Apply AI-enabled methods to accelerate research workflows while maintaining rigor and reproducibility.
• Provide training and workshops to HMS researchers on computational biology practices.

Skills

R/Python proficiency

Quantitative analytics

Communication skills

Independent work

Education

PhD in Bioinformatics/ Biostatistics/ CS

Tools

Git

Shiny/Connect

TensorFlow/PyTorch

Bioconductor

Job description

The Core for Computational Biomedicine (CCB) in the Department of Biomedical Informatics (DBMI) at Harvard Medical School (HMS) is looking for an experienced 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.

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Responsibilities include:

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• Collaboration on development and maintenance of scalable, reproducible pipelines
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• Collaborate with the CCB team to 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.
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• AI-enabled methods and applied research tooling
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• Apply knowledge of AI and computational research methods to 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.
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• Training, workshops, and internal enablement
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• Provide technical guidance 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.
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• Open-source software and biomedical data asset development
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• Building and maintaining 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.
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Basic Qualifications:

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• Minimum of five years' post-secondary education or relevant work experience.
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Additional Qualifications and Skills:

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• PhD in Bioinformatics, Biostatistics, Computer Science, Statistics or related field- strongly preferred.
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• Substantial experience in analyzing genetic, genomic, or image data.
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• Ability to program at a high level in R or Python.
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• Ability to work independently.
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• Experience with analyzing single-cell and spatial omics data.
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• Working knowledge of git or similar tools for scientific software development.
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• Experience writing data publishing tools that support user interaction such as RStudio's Shiny or Connect applications.
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• Experience with machine learning frameworks such as TensorFlow or PyTorch. Ability to work on teams.
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• Strong communication skills.
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Standard Hours/Schedule: 35 hours per week

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Visa Sponsorship Information: Harvard University is unable to provide visa sponsorship for this position.

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Pre-Employment Screening: Identity

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Staying Informed About Your Application: Due to the high volume of applications, we may not always be able to reach out right away, but you can track your status anytime through the Careers@Harvard portal.

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Work Format Details

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This position has been determined by school or unit leaders that some of the duties and responsibilities can be effectively performed at a non-Harvard location. The work schedule and location will be set by the department at its discretion and based upon operational needs. When not working at a Harvard or Harvard-designated location, employees in hybrid positions must work in a Harvard registered state in compliance with the University's Policy on Employment Outside of Massachusetts . Additional details will be discussed during the interview process. Certain visa types and funding sources may limit work location. Individuals must meet work location sponsorship req