Principal/Senior Data Scientist – Computational Genomics

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.

This is a unique opportunity for a data scientist to work on multi-omics data to drive transformative insights into drug discovery. You will have hands-on experience applying computational methods to real-world therapeutic discovery challenges.

As part of the Cross Indication team, you will work across multiple programme areas, applying computational techniques to multi-omics data. This team supports target identification and validation efforts, combining biological insights with state-of-the-art statistical and computational tools.

Your Responsibilities

• Develop and implement scalable computational workflows for the analysis of multi-omics and population genetics datasets.
• Lead multi-modal data integration efforts to uncover disease biology, prioritise mechanisms, and identify actionable targets.
• Design and apply statistical models for analysing genomics, transcriptomics, and other omics datasets.
• Partner closely with experimental and machine learning teams to validate hypotheses, interpret results, and guide downstream studies.
• Communicate findings clearly to internal stakeholders, including presenting methods, results, and recommendations.
• Contribute to publications, scientific communications, and project documentation, supporting scientific excellence and external visibility.

Qualifications

• PhD in genomics, computational biology, bioinformatics, or a related quantitative discipline.
• Post-PhD experience, ideally including time in an industry, biotech, or pharmaceutical environment.
• Strong track record in statistical genetics, computational biology, and multi-omics data analysis, including transcriptomics.
• 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.
• A background in statistical modelling and algorithm development.

Personal

• 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 have a direct impact on advancing our understanding of genetics and disease risk, supporting our mission to get transformative medicines to patients. Together, we’re not just doing research; we’re setting new standards in the field of machine learning and genetics. The patient is waiting!