Senior Data Scientist, Translational & Multiomics

Socket.dev; Dallas (TX); On-site; USD 120,000 - 170,000; Full time

Benefits offered by this job

PPO medical plan

Paid Time Off

Retirement Programs through TRS

Paid Parental Leave

Tuition Reimbursement

Job summary

UT Southwestern Medical Center in Dallas, TX, seeks a senior data scientist to lead analytic work across biomedical research programs, from study design to dissemination of results. The role emphasizes collaboration with PI and clinical teams, and the development of robust analytic strategies.

The position focuses on data integration, multiomics analysis, and publication-quality figures, with emphasis on reproducible pipelines in R and Python.

Qualifications

• PhD in data science, biostatistics, bioinformatics, computational biology, computer science, biomedical engineering, or a related quantitative field.
• Master's degree in a related quantitative or biological field may be considered with substantial experience.
• Bachelor's degree with demonstrated experience in broadly defined areas of bioinformatics.

Responsibilities

• Lead computational and quantitative sections of manuscripts and grant applications, and maintain analytic documentation.
• Independently analyze diverse omics and clinical datasets from raw files through interpretation.
• Develop scalable image-analysis workflows and integrate experimental data with clinical variables.
• Build reproducible analysis pipelines in R and Python with version control and containerized environments.
• Mentor trainees and staff in statistics, reproducible research, and data science.

Job description

UT Southwestern Medical Center in Dallas, TX, seeks a senior data scientist to lead analytic work across biomedical research programs, from study design to dissemination of results. The role emphasizes collaboration with PI and clinical teams, and the development of robust analytic strategies.

The position focuses on data integration, multiomics analysis, and publication-quality figures, with emphasis on reproducible pipelines in R and Python.