Senior Data Scientist – Statistical Genetics in London

About Relation

Relation is an end-to-end biotech company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. We leverage single-cell multi-omics directly from patient tissue, functional assays, and machine learning to drive disease understanding—from cause to cure. This year, we embarked on an exciting dual collaboration with GSK to tackle fibrosis and osteoarthritis, while also advancing our own internal osteoporosis programme. By combining our cutting‑edge ML capabilities with GSK’s deep expertise in drug discovery, this partnership underscores our commitment to pioneering science and delivering impactful therapies to patients. We are rapidly scaling our technology and discovery teams, offering a unique opportunity to join one of the most innovative TechBio companies. Be part of our dynamic, interdisciplinary teams, collaborating closely to redefine the boundaries of possibility in drug discovery. Our state‑of‑the‑art wet and dry laboratories, located in the heart of London, provide an exceptional environment to foster interdisciplinarity and turn groundbreaking ideas into impactful therapies for patients. We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does not discriminate on the grounds of gender, sexual orientation, marital or civil partner status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age. We cultivate innovation through collaboration, empowering every team member to do their best work and reach their highest potential. By joining Relation, you will become part of an exceptionally talented team with extraordinary leverage to advance the field of drug discovery. Your work will shape our culture, strategic direction, and, most importantly, impact patients’ lives.

The Opportunity

This is a unique opportunity for a Senior/Principal Scientist to lead and shape statistical and population genomics efforts to accelerate target identification and validation across multiple therapeutic areas. You will work with large-scale human genetics resources (e.g. biobanks and population cohorts) and apply cutting‑edge statistical genetics methodologies to generate actionable insights. As part of the Cross Indication team, you will operate at the interface of human genetics, computational biology, and machine learning, translating genetic evidence into target prioritisation frameworks and mechanistic hypotheses. You will play a key role in developing robust, scalable analysis pipelines and ensuring genetic insights are integrated into decision‑making across the organisation.

Your responsibilities

• Lead statistical and population genomics analyses using large-scale datasets to support target discovery and validation.
• Design and implement statistical genetics methodologies for target prioritisation, including approaches leveraging GWAS, fine‑mapping, colocalisation, polygenic risk, rare variant analyses, and functional annotation.
• Develop scalable computational workflows for reproducible genetics analysis, enabling robust and efficient delivery across multiple programmes.
• Integrate human genetics evidence with multi‑omics datasets (e.g. transcriptomics, proteomics) to uncover disease mechanisms and prioritise actionable targets.
• Partner closely with experimental, translational, and ML teams to validate hypotheses, interpret findings, and guide downstream decision‑making.
• Communicate results clearly and confidently to internal stakeholders, including presenting methods, results, risks/limitations, and recommendations.
• Contribute to publications, scientific communications, and project documentation, supporting scientific excellence and external visibility.

Professionally, you have

• PhD in statistical genetics, genomics, computational biology, bioinformatics, or a related quantitative field.
• Post‑PhD experience, ideally including time in an industry, biotech, or pharmaceutical environment.
• Deep expertise in statistical genetics and population genomics, including experience with large‑scale human genetic datasets and post‑GWAS analyses.
• High proficiency in Python (preferred) and R, with experience working in high‑performance computing environments.
• Ability to operate independently at a senior level, providing technical leadership and driving projects from concept through delivery.

Desirable knowledge or experiences

• Familiarity with single‑cell transcriptomics or patient‑derived datasets.
• Experience working in interdisciplinary teams within biotech or pharma settings.
• Knowledge of machine learning techniques applied to biological data.
• Experience with causal inference frameworks (e.g. Mendelian randomisation) to strengthen target validation.
• Strong understanding of the end‑to‑end drug discovery process and how genetic evidence informs decision‑making.

Personally, you are

• Inclusive leader and team player.
• Clear communicator.
• Driven by impact.
• Humble and hungry to learn.
• Motivated and curious.
• Impact‑driven and passionate about improving patient outcomes.
• Comfortable working in dynamic, fast‑paced environments.

Join us in this exciting role, where your contributions will directly impact advancing our understanding of genetics and disease risk, supporting our mission to deliver transformative medicines to patients. Together, we’re not just conducting research—we’re setting new standards in the fields of machine learning and genetics. The patient is waiting!