Data Scientist/Computational Biologist

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Why join Harvard Medical School?

Harvard Medical School's mission is to nurture a diverse, inclusive community dedicated to alleviating suffering and improving health and well-being for all through excellence in teaching and learning, discovery and scholarship, and service and leadership.

You’ll be at the heart of biomedical discovery, education, and innovation, working alongside world-renowned faculty and a community dedicated to improving human health. This is more than a job - it’s an opportunity to shape the future of medicine.

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.

Responsibilities include:

Collaboration on development and maintenance of scalable, reproducible pipelines

• 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.

AI-enabled methods and applied research tooling

• 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.

Training, workshops, and internal enablement

• 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.

Open-source software and biomedical data asset development

• 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.

Basic Qualifications:

• Minimum of five years’ post-secondary education or relevant work experience.

Additional Qualifications and Skills:

• 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.

• Standard Hours/Schedule: 35 hours per week
• Visa Sponsorship Information: Harvard University is unable to provide visa sponsorship for this position.
• Pre-Employment Screening: Identity
• 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.

Work Format Details

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 requirements prior to employment.

Salary Grade and Ranges

This position is salary grade level 057. Please visit Harvard's Salary Ranges to view the corresponding salary range and related information.

Benefits

Harvard offers a comprehensive benefits package that is designed to support a healthy work-life balance and your physical, mental and financial wellbeing. Because here, you are what matters. Our benefits include, but are not limited to:

• 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

Learn more about these and additional benefits on our Benefits & Wellbeing Page.

EEO/Non-Discrimination Commitment Statement

Harvard University is committed to equal opportunity and non-discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard's academic purposes.

Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university's non-discrimination policy. Harvard's equal employment opportunity policy and non-discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.