Senior Computational Genomics Scientist — Hybrid

Vertex Pharmaceuticals; San Diego (CA); Hybrid; USD 130,000 - 195,000; Full time

Job summary

Vertex Pharmaceuticals in San Diego is seeking a Senior Research Scientist in Computational Genomics to join the Data and Computational Sciences organization. You will work at the intersection of human genetics, genomics, and AI to accelerate therapies for serious diseases.

You will lead analyses from question to actionable recommendations and guide genomics use across discovery programs. Success requires scientific independence, collaboration, and the ability to communicate complex results to

Qualifications

• PhD with 3+ years post-doctoral or industry experience in relevant field.
• Proven ability to analyze, visualize, and interpret human genetics/genomics/NGS data.
• Experience applying computational methods to large-scale biological datasets.

Responsibilities

• Partner with cross-functional teams to define scientific questions and analyses.
• Design and interpret human genetic, genomic, and multi-omics studies for target discovery and biomarker development.
• Apply computational/statistical methods to integrate internal and public data.
• Communicate conclusions, limitations, and next steps clearly to diverse audiences.
• Shape genomics strategies across discovery programs with rigorous study design and analysis plans.
• Collaborate with computational and experimental scientists to leverage AI/ML for discovery.

Skills

Genomics knowledge

Data analysis

Communication

ML/AI interest

Collaborative

Education

PhD in computational biology / genomics / related field

Master's degree in related field

Tools

R

Python

Unix/Linux

Job description

Vertex Pharmaceuticals in San Diego is seeking a Senior Research Scientist in Computational Genomics to join the Data and Computational Sciences organization. You will work at the intersection of human genetics, genomics, and AI to accelerate therapies for serious diseases.

You will lead analyses from question to actionable recommendations and guide genomics use across discovery programs. Success requires scientific independence, collaboration, and the ability to communicate complex results to