Computational Biologist

Odyssey Therapeutics; Boston (MA); On-site; USD 110,000 - 170,000; Full time

Job summary

Odyssey Therapeutics seeks a Computational Biologist to support target discovery, translational biology, biomarker development, and clinical data analysis across autoimmune and inflammatory programs. You will analyze omics and clinical datasets to generate actionable insights for therapeutic hypotheses, patient stratification, and clinical strategies.

Collaboration with multiple teams and external partners is essential.

Qualifications

• Ph.D. (or equivalent) in Computational Biology, Bioinformatics, Genetics, Immunology, Systems Biology, or a related discipline.
• 2+ years of experience developing bioinformatics pipelines and applying computational approaches to immunology or drug discovery.
• Deep expertise in computational biology, bioinformatics, and statistical analysis of large-scale datasets.
• Experience analyzing GWAS, WGS, and other human genetics datasets.
• Experience with public genomics resources (GEO, UK Biobank, All of Us, Open Targets, FinnGen, etc.).
• Expertise in bulk and single-cell omics pipelines (RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, etc.).
• Proficiency in R and/or Python; version control and reproducible workflows.
• Strong communication and collaboration across cross-functional teams.
• Experience with translational medicine or clinical development is a plus.

Responsibilities

• Analyze internal and public omics datasets to support target discovery and translational research.
• Develop and optimize bioinformatics pipelines for multi-omics data analysis.
• Analyze diverse human datasets to identify pathways, targets, and biomarkers.
• Evaluate clinical data to find biomarkers linked to response, resistance, and progression.
• Collaborate with Discovery Biology, Translational Medicine, and Clinical Development to integrate data.
• Present findings to cross-functional teams and contribute to reports, publications, and communications.

Skills

Bioinformatics pipelines

Computational biology

Statistical analysis

R

Python

GWAS/WGS analysis

Omics data integration

Collaboration across teams

Scientific communication

Education

Ph.D. in Computational Biology or related

Tools

Git

Job description

The opportunity:

Odyssey Therapeutics is seeking a Computational Biologist to support target discovery, translational biology, biomarker development, and clinical data analysis across our portfolio of autoimmune and inflammatory disease programs.

This role will work closely with Discovery Biology, Translational Medicine, Clinical Development, and external collaborators to analyze and integrate genomic, transcriptomic, and clinical datasets to generate actionable biological insights that support therapeutic hypothesis generation, patient stratification, and clinical development strategies.

Your primary objectives will be:

• Analyze internal and publicly available omics datasets to support target discovery, translational research, and therapeutic hypothesis generation.


• Develop, maintain, and optimize robust bioinformatics pipelines for the analysis of multi-omics datasets.


• Analyze GWAS, eQTL, transcriptomic, proteomic, and other human disease datasets to identify disease-relevant pathways, therapeutic targets, and biomarkers.


• Evaluate clinical and translational datasets to identify biomarkers associated with therapeutic response, resistance, and disease progression.


• Collaborate closely with Discovery Biology, Chemistry, Translational Medicine, and Clinical Development teams to integrate diverse datasets and generate actionable biological insights.


• Present scientific findings to cross-functional teams and contribute to internal reports, scientific presentations, publications, and external communications.

About you:

• Ph.D. (or equivalent experience) in Computational Biology, Bioinformatics, Genetics, Immunology, Systems Biology, or a related discipline.


• 2+ years of experience developing bioinformatics pipelines and applying computational approaches to immunology and/or drug discovery in an industry or academic setting.


• Deep expertise in computational biology, bioinformatics, and statistical analysis of large-scale biological datasets.


• Experience analyzing GWAS, whole-genome sequencing (WGS), and other human genetics datasets.


• Experience working with large public genomics resources such as GEO, ArrayExpress, UK Biobank, All of Us, Open Targets, FinnGen, or similar repositories.


• Demonstrated expertise in developing pipelines for bulk and single-cell omics technologies, including RNA-seq, scRNA-seq, CITE-seq, ATAC-seq, ChIP-seq, WGS, and WES.


• Strong proficiency in R and/or Python, with experience using version control and developing reproducible, standardized analysis workflows.


• Ability to rapidly learn and apply new computational methods and emerging omics technologies.


• Broad understanding of molecular biology, cell biology, biochemistry, and translational research.


• Familiarity with autoimmune, inflammatory, or immune-mediated diseases.


• Experience managing and analyzing large, complex datasets across multiple research programs.


• Proven ability to work collaboratively with computational scientists, biologists, chemists, and cross-functional project teams.


• Strong scientific communication skills, with the ability to independently perform analyses and clearly communicate findings to both computational and non-computational audiences.


• Demonstrated scientific contributions to computational biology and drug discovery through publications, presentations, or other impactful research.


• Creative, scientifically rigorous, and motivated to solve challenging biological problems in a collaborative environment.


• Experience supporting translational medicine, biomarker discovery, or clinical development programs is preferred.


• Experience integrating multi-modal omics datasets and applying AI or machine learning approaches to biological data analysis is preferred.