Senior Data Scientist, Translational Multi-Omics

University of Texas Southwestern Medical Center; Dallas (TX); On-site; USD 120,000 - 170,000; Full time

Benefits offered by this job

PPO medical plan

Paid Time Off

Tuition Reimbursement

Public Service Loan Forgiveness (PSLF)

Wellness programs

Job summary

UT Southwestern Medical Center in Dallas, TX seeks a senior Data Scientist to lead computational analyses for biomedical and translational research. Collaborate with PI, clinicians, and scientists to design analytic strategies and integrate multiomic data for publication-quality outputs.

The role focuses on modeling, data integration, and reproducible pipelines in R and Python, enabling mechanistic insights and clinically meaningful subgroups across multiple programs.

Qualifications

• PhD in computer science, bioinformatics, (bio)statistics, (bio)mathematics, physics, electrical engineering, or related field.
• Master's Degree (MS) in Computer Science, Bioinformatics, (Bio)statistics, (Bio)mathematics, Physics, Electrical Engineering, or related field.
• Bachelor's Degree (BS) with demonstrated experience in broadly defined areas of bioinformatics.

Responsibilities

• Lead computational analyses and develop data-driven strategies in biomedical research.
• Independently analyze single-cell and bulk transcriptomic, epigenomic, spatial, proteomic, metabolomic, and imaging datasets.
• Develop scalable image-analysis workflows and integrative analyses across multiomic data.
• Mentor trainees and staff in statistics, computational biology, and reproducible research.
• Manage multiple projects with priorities and milestones.

Skills

Data analysis

Software development

Bioinformatics

Biostatistics

Computational biology

Machine learning

Education

PhD in computer science or bioinformatics or related field

MS in computer science or bioinformatics or related field

BS with demonstrated experience in bioinformatics

Job description

UT Southwestern Medical Center in Dallas, TX seeks a senior Data Scientist to lead computational analyses for biomedical and translational research. Collaborate with PI, clinicians, and scientists to design analytic strategies and integrate multiomic data for publication-quality outputs.

The role focuses on modeling, data integration, and reproducible pipelines in R and Python, enabling mechanistic insights and clinically meaningful subgroups across multiple programs.