Bioinformatics Data Scientist: ML & Cloud Pipelines

UCSF Health, AG; San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

UCSF Health seeks a Bioinformatics Programmer/Data Scientist to analyze large-scale biological and clinical data, develop machine learning and statistical models, and support data management across cloud and on‑premises infrastructure.

Under the PI, you will maintain bioinformatic databases, build analytic pipelines using R, Python, Go, SQL, and Docker, and contribute to discovery analyses; opportunities for authorship on manuscripts exist.

Qualifications

• Bachelor's degree in biological science, computational / programming, or related area and / or equivalent experience / training.
• MS or greater in a related science or an equivalent combination of education and experience.
• PhD in bioinformatics, biomedical engineering, computer science or related area.

Responsibilities

• Develops and utilizes computational tools to analyze biological or research data.
• Designs and builds machine learning and statistical models.
• Maintains computational infrastructure and data pipelines across cloud and on‑premises environments.
• Writes and maintains analytic pipelines in languages such as R, Python, Go, Rust, shell, SQL, WDL, and uses Docker.
• Maintains bioinformatic databases and supports data access for discovery and replication analyses.
• Involves data analysis, potential authorship on publications, and collaboration with the PI.

Skills

Bioinformatics methods

Biostatistics

Systems programming

Databases

R programming

Python programming

Data pipelines

Cloud data management

Communication

Time management

Education

Bachelor's degree in biological sciences / computational fields

MS or higher in related field

PhD in biomedical or CS fields

Tools

Docker

Job description

UCSF Health seeks a Bioinformatics Programmer/Data Scientist to analyze large-scale biological and clinical data, develop machine learning and statistical models, and support data management across cloud and on‑premises infrastructure.

Under the PI, you will maintain bioinformatic databases, build analytic pipelines using R, Python, Go, SQL, and Docker, and contribute to discovery analyses; opportunities for authorship on manuscripts exist.