Data Scientist III, Mineral Metabolism, Levi Lab

About the role

The Levi Laboratory at UT Southwestern Medical Center studies how immune, stromal, vascular, lymphatic, neural, epithelial and mesenchymal cell populations interact after injury and in disease, using animal models, human biospecimens, imaging and multiomic technologies. This position is for a senior data scientist who leads the analytic parts of several research programs, from study design and data acquisition through quality control, modeling, biological interpretation, validation and dissemination. The role is primarily computational, working closely with experimental and clinical teams.

Key responsibilities

• Design data-driven research strategies with the PI and collaborators, covering outcome definition, sample selection, controls, replication, power, data harmonization, batch mitigation and validation plans.
• Analyze complex biomedical datasets (single-cell or bulk transcriptomics, epigenomics, spatial, proteomics, metabolomics, cytometry, imaging, micro-CT, clinical data) in bioinformatics, quantitative image analysis or machine learning.
• Build, document and maintain reproducible pipelines in R and/or Python, using version control, containers and high-performance or cloud computing.
• Set up laboratory standards for metadata, data dictionaries, sample tracking, code review, backups, controlled access, privacy and FAIR data practices.
• Create publication-quality figures, dashboards, tables and data narratives for manuscripts, grants and presentations, and lead computational sections of manuscripts and grant applications.
• Mentor trainees and staff, manage multiple concurrent projects and present findings at meetings and conferences.

Required profile

• Ph.D. in a quantitative or biological field, with 2 years of post-graduation experience in data analysis and/or scientific software development; or a Master's degree with 4 years of relevant experience; or a Bachelor's degree with 6 years of progressively responsible experience.
• Demonstrated ability to lead complex biomedical analyses in at least one of bioinformatics, quantitative image analysis or machine learning.
• Record of peer-reviewed publications and, if available, a GitHub profile or other portfolio of reproducible code.

Required skills

• Advanced R and Python, with Git and reproducible documentation.
• Statistical inference and experimental design, including regression, multiple-testing correction, batch effects and model evaluation.
• Preferred: single-cell or spatial transcriptomics, metabolomics, proteomics, imaging mass cytometry, micro-CT, Linux, shell scripting, containerized environments and interpretable machine-learning models.

What we offer

• PPO medical plan available day one at no cost for full-time employee-only coverage, with 100% coverage for preventive care.
• Paid time off, paid parental leave, retirement programs through TRS, wellness programs and tuition reimbursement.
• Public Service Loan Forgiveness (PSLF) qualified employer.