About the Job

The Scientist I, Computational Discovery contributes to the early innovation of novel bioinformatics methods and genomic signatures in oncology. Leveraging Foundation Medicine’s FoundationCORE dataset of 800,000+ samples and the Flatiron Health-Foundation Medicine joint Clinico-Genomic Database of 100,000+ samples with annotated clinical outcomes, this role explores novel patterns in cancer biology. The position plays a key role in conducting original research, generating insights, and preparing high-impact scientific abstracts, presentations, and peer-reviewed manuscripts. The work drives foundational understanding that supports clinical diagnostics and translational research in oncology.

In addition to research, this role develops sub-specialization in the data architecture supporting the team’s efforts, including pipeline workflow development, cloud-based data storage, and maintaining data quality and integrity. The ideal candidate will thrive at the intersection of cancer biology, computational science, and data infrastructure.

Key Responsibilities

Develop and evaluate potential signatures and biomarkers using large-scale datasets; investigate genomic mechanisms underlying oncogenesis. Apply statistical analyses, analyze genomic data via HPC clusters, and improve assay performance. Organize, visualize, and interpret data in a high-throughput, data-intensive environment. Collaborate with internal cross-functional teams — including R&D, Medical, Commercial, Biopharma, and Regulatory — and engage with external collaborators to support enterprise goals. Work closely with molecular biologists, computational scientists, and regulatory teams to inform the feasibility and planning of translational next-generation sequencing (NGS) assays. Maintain awareness of current bioinformatics methods and diagnostic oncology literature. Prepare and present results in internal meetings and contribute to scientific literature. Design and refine bioinformatics algorithms, workflows, and analysis pipelines; manage cloud-based data infrastructure and ensure data quality. Build, maintain, and enhance internal data workflows and computational pipelines; implement and uphold best practices in data architecture and cloud-based data systems Other duties as assigned.

Qualifications:

Basic Qualifications:

Bachelor’s degree in related field and 3+ years of research experience preferred in the life sciences industry; OR, Master’s and 2+ research experience preferred in the life sciences industry; OR, PhD and no experience

Preferred Qualifications:

1+ years of industry or post-doctoral research experience in cancer biology, bioinformatics, or a related field using NGS data Proficiency in Unix or Unix-like operating systems; proficiency in one or more programming languages such as Python, R, SQL, or similar scientific computing languages; familiarity with other programming or scripting languages Familiarity with cloud computing platforms (e.g. AWS) Experience using version control tools (e.g. Git) Experience working with public datasets (e.g., TCGA, cBioPortal, Genomic Data Commons) Competence in basic statistical methods and applications in bioinformatics Fundamental understanding of molecular biology and NGS principles (e.g., DNA-seq, library prep, target enrichment) Effective collaboration and communication skills, including scientific writing and presenting data to multidisciplinary teams Understanding of HIPAA and the importance of patient data privacy Commitment to reflect FMI's values of passion, patients, innovation, and collaboration

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