Bioinformatics Data Scientist: Cloud Pipelines & Genomics

University of California, San Francisco; San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

University of California, San Francisco is seeking a Bioinformatics Programmer/Data Scientist to develop and maintain pipelines for large-scale medical data analysis. You will implement pipelines in R, Python, Go, Rust, shell, SQL, WDL and use tools like Docker, with cloud and on-premises compute.

You will work under the PI, perform bioinformatic analyses including variant calling and annotation, contribute to manuscripts, and help lead authorship teams while learning new techniques across cloud

Qualifications

• Bachelor's degree in biological science, computational/programming, or related area.
• 12+ months of demonstrated work experience using medical or health-related data, including ETL pipelines and data analysis.
• Working knowledge of bioinformatics methods and data structures.
• Working knowledge of biostatistics and basic statistical testing.
• Working knowledge of systems programming and databases.
• Ability to manage time and meet deadlines on assigned parts of projects.
• Fluency with R or Python for statistical programming.

Responsibilities

• Design, develop, debug, and utilize programs to extract, transform, and load data for analysis.
• Develop data pipelines to standardize and automate data processing steps.
• Build and run programs to extract imaging, biosignals, and medical data from clinical systems.
• Perform data quality control and statistical analyses.
• Manage cloud and containerized environments (Docker, cloud platforms).
• Write documentation and comments for analyses, code, and pipelines.
• Contribute to manuscript preparation and dissemination of results.

Skills

Python

R

Go

Rust

SQL

WDL

shell

Education

Bachelor's degree

Tools

AWS

Azure

GCP

plink2

Git

Job description

University of California, San Francisco is seeking a Bioinformatics Programmer/Data Scientist to develop and maintain pipelines for large-scale medical data analysis. You will implement pipelines in R, Python, Go, Rust, shell, SQL, WDL and use tools like Docker, with cloud and on-premises compute.

You will work under the PI, perform bioinformatic analyses including variant calling and annotation, contribute to manuscripts, and help lead authorship teams while learning new techniques across cloud