Computational Biologist, Contractor​/Consultant

Preventive is a public benefit corporation focused on rigorous, evidence-based research to prevent disease before birth. The organization’s mission is to evaluate whether advanced gene-editing technologies can be used safely and responsibly to correct serious genetic conditions in future children. Preventive operates at the intersection of genomics, ethics, and public health, aiming to shape standards for responsible innovation in reproductive medicine.

Team members collaborate with leading experts to generate data and insights that can inform clinical practice, regulation, and societal dialogue.

The Computational Biologist, Contractor/Consultant will work full time on-site in San Francisco, CA, collaborating closely with experimental scientists and clinical researchers. This role involves designing and implementing computational pipelines to analyze genomic and other high-dimensional biological data related to gene-editing safety and efficacy. Day-to-day responsibilities include developing and validating statistical models, performing data quality control, integrating multi-omic datasets, and interpreting results in the context of disease prevention.

The contractor/consultant will prepare clear reports, visualizations, and presentations for internal stakeholders, contribute to research publications, and support the development of best practices for data management and reproducible analysis. The role also includes staying current with relevant literature and tools, and recommending methods that strengthen Preventive’s research program.

• Strong quantitative skills, including Statistics and Data Analysis, applied to complex biological datasets.
• Experience in Data Science, including building reproducible workflows, using modern data tools, and working with large-scale data.
• Demonstrated expertise in Bioinformatics, such as genomic data processing, variant analysis, and pipeline development.
• Proven track record in Research, including hypothesis-driven studies, rigorous methodology, and scientific communication.
• Proficiency in relevant programming languages (e.g., Python, R) and familiarity with computational biology libraries and tools.
• Background in computational biology, genomics, biostatistics, or a related field; advanced degree (MS or PhD) preferred or equivalent experience.
• Experience working with gene-editing, sequencing, or other high-throughput technologies is a plus.
• Ability to collaborate in an interdisciplinary environment, communicate clearly with non-technical partners, and adhere to high ethical standards in research.