Remote Genomics & Multimodal Data Scientist

Planet Pharma; South San Francisco (CA); Hybrid; USD 62,000 - 74,000; Full time

Job summary

Planet Pharma in the United States seeks a highly independent computational scientist in genetic epidemiology and statistical genetics to develop and apply analytical methods for integrating genetic, genomic, and clinical data. Hybrid or remote US-friendly time zone, 1-year contract with extension possible.

Responsibilities include analyzing large datasets, developing multimodal data integration approaches, and implementing ML to link imaging and omics data.

Qualifications

• PhD in Statistical Genetics, Computational Biology, Bioinformatics, or Genetic Epidemiology, or Masters with experience
• Fluent in R, Python, and shell scripting; some C++ familiarity
• Experience with Git and HPC environments (e.g., SLURM)
• Extensive experience in large-scale genetic/genomic data analysis
• Ability to work independently and meet deadlines with good communication

Responsibilities

• Collaborate with scientists in Human Genetics department to analyze large datasets of genetic, genomic, and clinical data from internal studies (including our clinical trials and high throughput screens), collaborations with academic and industry partners, and public external data sets
• Develop analytical approaches to integrate and interpret these data, delivering insights into disease biology to propel our translational goals
• Implement novel machine learning algorithms to understand associations between imaging and omics data
• Coordinate the intake and preparation of new datasets as they become available for analysis
• Document process, findings, and code
• Present findings to the department and cross-functional collaborators and contribute to publications

Skills

R

Python

Shell scripting

Data analysis

Education

PhD in Statistical Genetics / Computational Biology / Bioinformatics / Genetic Epidemiology

Masters with significant experience

Tools

Git

SLURM

C++

Job description

Planet Pharma in the United States seeks a highly independent computational scientist in genetic epidemiology and statistical genetics to develop and apply analytical methods for integrating genetic, genomic, and clinical data. Hybrid or remote US-friendly time zone, 1-year contract with extension possible.

Responsibilities include analyzing large datasets, developing multimodal data integration approaches, and implementing ML to link imaging and omics data.