Data Scientist

University Overview

The University of Pennsylvania, the largest private employer in Philadelphia, is a world-renowned leader in education, research, and innovation. This historic, Ivy League school consistently ranks among the top 10 universities in the annual U.S. News & World Report survey. Penn has 12 highly-regarded schools that provide opportunities for undergraduate, graduate and continuing education, all influenced by Penn’s distinctive interdisciplinary approach to scholarship and learning. As an employer Penn has been ranked nationally on many occasions with the most recent award from Forbes who named Penn one of America’s Best Large Employers in 2023.

Penn offers a unique working environment within the city of Philadelphia. The University is situated on a beautiful urban campus, with easy access to a range of educational, cultural, and recreational activities. With its historical significance and landmarks, lively cultural offerings, and wide variety of atmospheres, Philadelphia is the perfect place to call home for work and play.

The University offers a competitive benefits package that includes excellent healthcare and tuition benefits for employees and their families, generous retirement benefits, a wide variety of professional development opportunities, supportive work and family benefits, a wealth of health and wellness programs and resources, and much more.

Posted Job Title

Data Scientist

Job Profile Title

Job Description Summary

The Data Scientist will lead and support advanced computational biology and biomedical informatics research, working in close partnership with principal investigators and collaborators. A primary focus will be integrating and analyzing large-scale clinical, genomics, proteomics, imaging, and informatics data, with the Penn Medicine Biobank (PMBB) as a central resource.

The Data Scientist will assess project feasibility, contribute to study design, and oversee analytic execution. They will develop and maintain computational pipelines, ensure methodological rigor and reproducibility, and mentor trainees and staff in computational approaches. Additional responsibilities include contributing to manuscripts, grant applications, and presentations at scientific meetings.

This is a leadership opportunity at the intersection of data science and biomedical research, enabling high-impact discoveries and building shared infrastructure that accelerates future studies

Job Description

The Data Scientist will lead and support advanced computational biology and biomedical informatics research, working in close partnership with principal investigators and collaborators. A primary focus will be integrating and analyzing large-scale clinical, genomics, proteomics, imaging, and informatics data, with the Penn Medicine Biobank (PMBB) as a central resource.

The Data Scientist will assess project feasibility, contribute to study design, and oversee analytic execution. They will develop and maintain computational pipelines, ensure methodological rigor and reproducibility, and mentor trainees and staff in computational approaches. Additional responsibilities include contributing to manuscripts, grant applications, and presentations at scientific meetings.

This is a leadership opportunity at the intersection of data science and biomedical research, enabling high-impact discoveries and building shared infrastructure that accelerates future studies

Job Responsibilities

• Lead the design, development, and execution of computational genomics, multi-omics integration, and biomedical informatics projects in collaboration with the principal investigators.
• Collaborate with PIs and PMBB Clinical Informatics and Genomics Core on projects that leverage imaging-derived phenotypes, including working with AI and deep learning methods to extract features from medical images and integrating these into downstream analyses.
• Develop and maintain computational pipelines for phenotype generation, data harmonization, and integration across clinical, imaging, and genomic datasets.
• Assess feasibility, efficiency, and study design for proposed projects, providing input on timelines and resource planning.
• Oversee dat