Computational Biologist / Data Scientist
About The Position
Hexagon Bio leverages its proprietary platform to discover new medicines by mining microbial genomes for their therapeutic potential. Our interdisciplinary team combines expertise in genomics, synthetic biology, machine learning, and drug discovery to accelerate the development of next-generation therapeutics. We are seeking a Computational Biologist / Data Scientist with deep expertise in evolutionary biology and natural product genomics to join our data science and genomics team. In this role, you will analyze large-scale microbial genomic datasets to identify, characterize, and prioritize biosynthetic gene clusters (BGCs) that encode novel chemistry. You will apply comparative genomics and evolutionary frameworks to Hexagon Bio’s proprietary collection of over 100,000 fungal genomes, transforming genomic patterns into actionable hypotheses that drive experimental discovery and therapeutic development. You will work closely with biologists, chemists, and engineers to connect genomic insights with experimental design, pathway engineering, and downstream chemical and biological validation. This is an onsite role at Hexagon’s office in Menlo Park, California.
Requirements
- PhD in Computational Biology, Genomics, Bioinformatics, or a related field.
- Demonstrated expertise in biosynthetic gene cluster prediction and natural product genomics.
- Strong background in genome evolution and evolutionary biology, particularly in non-model organisms.
- Proficiency in Python for data analysis, pipeline development, and algorithm implementation.
- Experience developing statistical or computational approaches to extract biological insight from genome-scale data.
Nice To Haves
- Experience analyzing or interpreting metabolomic data in the context of natural product discovery is a plus.
- Prior exposure to experimental microbiology, metabolomics, or natural products chemistry is a plus.
- Experience with cloud computing platforms (e.g., Google Cloud, AWS) is a plus.
- Experience building production-quality software or scalable analysis pipelines is a plus.
- Experience applying or developing machine learning methods is a plus, but not required.
Responsibilities
- Develop and apply computational methods to predict, classify, and prioritize biosynthetic gene clusters from large genomic datasets.
- Perform comparative genomics and evolutionary analyses across diverse, non-model fungal and bacterial species.
- Apply evolutionary and phylogenetic frameworks to identify novel biosynthetic potential and guide discovery strategy.
- Build, maintain, and scale robust Python-based pipelines for genome mining and data analysis.
- Integrate genomic insights with chemical, biological, and metabolomic data to support compound discovery and annotation.
- Collaborate cross-functionally to translate computational results into experimentally testable hypotheses and program decisions.
- Communicate findings clearly through analyses, visualizations, and presentations to multidisciplinary teams.
Benefits
- A collaborative, interdisciplinary environment with strong scientific ownership and impact.
- A transparent culture supported by regular All Hands meetings.
- Competitive compensation, equity, and comprehensive benefits.
- Opportunities for rapid growth and career development.
- Support for attending scientific conferences and external collaborations.
- Access to Menlo Park Labs amenities, including shuttle service, gym, climbing wall, pool, sports courts, café, bike storage, and EV charging.
- Team-building events such as Hexagon Happy Hours and company celebrations.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
Ph.D. or professional degree
Number of Employees
51-100 employees
