STATISTICAL GENETICS
TALENT SOLUTIONS
At Harnham, we specialize in recruiting statistical geneticists who apply statistical methods to genetic data, driving advancements in fields such as genomics, personalized medicine, and genetic epidemiology.
Statistical geneticists are in high demand for their expertise in statistical analysis, genetic data interpretation, and proficiency with tools like PLINK, R, and Python. Skills in genome-wide association studies (GWAS), quantitative trait loci (QTL) mapping, and bioinformatics are particularly valued.
WHY
HARNHAM?
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- Focused Expertise: With over 17 years of experience, we understand the specific qualifications needed for success in statistical genetics roles.
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- Global Talent Pool: Our network of statistical genetics professionals spans across the United States, Europe, and the United Kingdom.
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- Tailored Recruitment Solutions: We offer recruitment services that are designed to meet your specific needs, whether for contract, permanent, or executive roles.
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OUR
SERVICES
- ATD - Rockborne: Access to newly trained statistical geneticists with cutting-edge skills, ready to contribute to your team.
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- Contract / Freelance: Flexible staffing options to address immediate project needs.
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- Full-Time / Direct Hiring: Sourcing permanent team members to support your long-term research objectives.
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- Executive Search: Identifying leadership talent to drive your statistical genetics initiatives.
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- GenAI, Prompt, LLM Training: Customized training programs to ensure your team remains at the forefront of statistical genetics.
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Partner with Harnham: Whether you're seeking to build a team or advance your career in statistical genetics, Harnham has the expertise to help you succeed. Contact us to discuss your recruitment needs.
For Job Seekers: Interested in statistical genetics roles? Explore the latest opportunities and take the next step in your career.
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JOBS
LATEST
OPPORTUNITIES
Harnham are a specialist Data & AI recruitment business with teams that only focus on niche areas.
ML Scientist
San Francisco
$200000 - $280000
+ Life Science Analytics
PermanentSan Francisco, California
To Apply for this Job Click Here
ML Scientist / Researcher
Oncology AI · Foundation Models · Life Sciences
Remote
About the Role
We are building foundation models trained on human tumor biology – one of the most consequential and technically demanding challenges at the intersection of AI and medicine. As an ML Scientist, you will be a core research contributor designing and training these models across multimodal omics datasets, partnering closely with biologists and fellow research scientists to advance the state of the art in oncology AI.
This is a research-forward role for scientists who want their work to matter. We are looking for people with a track record of research excellence – those who have gone deep on model architecture, training dynamics, and rigorous experimental design. If you have built models from the ground up and published findings, we want to talk.
What You’ll Do
- Design and train large-scale foundation models on multimodal biological datasets, including genomics, transcriptomics, and other omics modalities
- Collaborate deeply with computational biologists, research scientists, and domain experts to translate biological questions into tractable modeling problems
- Drive the full research lifecycle: hypothesis formation, experimental design, model development, and rigorous analysis of results
- Contribute to agentic AI systems that reason over complex biological data
- Communicate findings internally and, where appropriate, through peer-reviewed publication
What We’re Looking For
Must-Haves
- Strong research background, typically evidenced by a PhD in machine learning, computational biology, statistics, physics, or a related quantitative field – or equivalent industry research experience
- Demonstrated ability to build and train models end-to-end, including experimental analysis and iteration
- Research excellence: first-author publications at top ML, AI, or computational biology venues are a strong positive signal
- Deep familiarity with foundation model concepts: pretraining, self-supervised learning, attention mechanisms, and large-scale training
- Comfort working at the intersection of biology and machine learning – even without a formal biology degree
Nice-to-Haves
- Experience with biological or omics data (genomics, proteomics, pathology imaging, etc.)
- Prior work in multimodal learning or multi-omics integration
- Familiarity with agentic AI systems or tool-use frameworks
- Background in oncology or disease biology
What This Role Is Not
This is not a production ML engineering or MLOps role. We are not looking for candidates whose primary experience is model deployment, serving infrastructure, or engineering-heavy systems work. The emphasis here is firmly on research depth and model development.
Compensation & Location
Base Salary: $250,000 – $288,000 (depending on experience) + equity
Location: Remote-friendly; office in South San Francisco, CA

To Apply for this Job Click Here
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