Principal Data Scientist; PopGen Modeling

I am partnering with a fast-growing, well-funded biotechnology company that is applying advanced AI and machine learning to accelerate drug discovery and translational research. This position will work across computational biology, population genetics, and modern data science, and is building a next-generation analytics platform to support therapeutic innovation.

We are seeking a Principal Data Scientist with deep experience in genomics and biological data modeling to play a hands-on role across research projects and platform development.

• Design, develop, and deploy advanced data science and machine learning models using complex biomedical datasets
• Work with population genetics, genomics, and multi-omics data to support target discovery, patient stratification, and biological insight generation
• Build and extend internal analytics platforms and reusable modeling frameworks
• Apply simulation-based and statistical modeling approaches to biological and genomic problems
• Collaborate closely with distributed scientific and technical teams
• Communicate complex analytical results clearly to both technical and non-technical stakeholders
• Contribute to shaping data science best practices, technical direction, and project execution

• PhD or MS with significant experience in a quantitative or life sciences discipline such as computational biology, bioinformatics, genetics, statistics, computer science, or engineering
• Approximately 5 to 8 plus years of post-graduate experience in life sciences analytics within biotech, pharma, consulting, or advanced academic research environments
• Strong hands-on experience with genomics and or multi-omics data, including population genetics, RNA sequencing, GWAS, WGS, or related data types
• Demonstrated proficiency in Python and modern data science tooling
• Experience applying machine learning or AI techniques to biological or healthcare datasets
• Comfort working with large-scale data and high-performance or cloud computing environments
• Ability to independently lead projects and collaborate across scientific and technical teams
• Excellent communication skills and the ability to translate complex analyses into actionable insights

• Experience with simulation-based modeling or evolutionary or population genetic frameworks
• Applied experience with NLP or large language models in a scientific or healthcare context
• Background in causal inference, graph-based methods, or multimodal modeling
• Cloud experience such as AWS or Google Cloud
• Experience supporting client-facing or cross-functional analytical projects

If you are excited about applying advanced data science to real-world biological problems and want to have a meaningful impact in drug discovery, this role offers the opportunity to work on intellectually challenging problems alongside a highly technical and collaborative team.

If you would be interested in hearing more, email me at  or give me a call at . Please note, this is not a contract opportunity, and my client will not be employing a candidate on a C2C or 1080 basis.