Oncology Bioinformatics Scientist | Data Pipelines & NGS

Foundation Medicine; Boston (MA); Hybrid; USD 113,000 - 133,000; Full time

Benefits offered by this job

Annual bonus

Comprehensive benefits

Hybrid work model

Job summary

Foundation Medicine in Boston, MA is seeking a Computational Biologist I to join our oncology bioinformatics team. You will help develop novel signatures and genomic biomarkers using large-scale datasets and contribute to high-impact abstracts, presentations, and manuscripts.

You will also help design data architectures, pipelines, and cloud-based storage, ensuring data quality while collaborating with R&D, Medical, Commercial, and Regulatory teams to translate findings into clinical context.

Qualifications

• Bachelor’s degree in related field and 6+ years of research experience in life sciences, or Master’s with 2+ years, or PhD with no experience.
• Proficiency in Unix-like OS and programming languages (Python, R, SQL) and cloud experience (AWS).
• Experience with public datasets (TCGA, Genomic Data Commons) and bioinformatics analyses.

Responsibilities

• Develop and evaluate potential signatures and biomarkers using large-scale datasets.
• Apply statistical analyses and analyze genomic data on HPC clusters.

Skills

Python

R

SQL

Unix

AWS

Git

Public datasets

Statistical methods

Bioinformatics

Scientific writing

Education

Bachelor's degree in related field

Master's degree in related field

PhD in a life sciences/related field

Tools

HPC clusters

Genomic Data Commons

TCGA data portals

Job description

Foundation Medicine in Boston, MA is seeking a Computational Biologist I to join our oncology bioinformatics team. You will help develop novel signatures and genomic biomarkers using large-scale datasets and contribute to high-impact abstracts, presentations, and manuscripts.

You will also help design data architectures, pipelines, and cloud-based storage, ensuring data quality while collaborating with R&D, Medical, Commercial, and Regulatory teams to translate findings into clinical context.