Senior Data Scientist - Single Cell & Spatial in London

Relation is a sector defining TechBio 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 from patient tissue, functional assays, and machine learning to drive disease understanding, from cause to cure. We are scaling rapidly and building a team of exceptional individuals to push the boundaries of drug discovery. You will work in highly interdisciplinary teams where biology, computation, and engineering come together to solve complex problems that have not been solved before. Our state‑of‑the‑art wet and dry labs in the heart of London are designed to accelerate this integration and translate insight into impact.

This is a unique opportunity for a senior data scientist to work on multi-omics and perturbational data to drive transformative insights into drug discovery. As a member of the Single Cell and Spatial Omics team, and embedded within one of the ML research teams, you will contribute advanced data analysis and domain expertise to challenge ML models that aim to predict and explain cellular decision‑making in disease.

Day to day, you will:

• Develop and implement computational workflows for integrating and analysing multi-omics data.
• Design statistical models for analysing transcriptomics and other omics datasets.
• Use domain and data insights to design meaningful and challenging evaluation tasks for ML models.
• Collaborate closely with ML modellers to develop model architectures.
• Work with experimental teams to design and validate computational hypotheses.
• Present findings and methodologies to internal stakeholders and contribute to publications.

Professionally, you will have:

• A PhD in computational biology, bioinformatics, or a related quantitative field.
• Extensive experience in multi-omics data analysis, including transcriptomics.
• Proficiency in Python and familiarity with high‑performance computing environments.

Bonus Experience:

• Familiarity with single-cell transcriptomics or patient‑derived datasets.
• Knowledge of ML techniques applied to biological data.
• A background in statistical modelling and algorithm development.
• Experience working in interdisciplinary teams.

Personally, you are:

• Comfortable working in a matrixed environment, balancing multiple stakeholders and contributing effectively across teams.
• Taking ownership of your work, proactively seeking opportunities to contribute, and enabling others to do their best work.
• Communicating openly and directly, giving and receiving feedback constructively, and handling challenging conversations with respect.
• Actively seeking out diverse perspectives, building strong working relationships, and contributing to shared goals across teams.
• Embracing challenges with openness and resilience, setting high standards for yourself, and striving to deliver meaningful outcomes.

Working style & culture at Relation:

At Relation, we operate in a matrixed, interdisciplinary environment, where impact is driven through collaboration across scientific, technical, and operational domains. We collaborate, and you will partner with colleagues across multiple teams and projects, contributing your expertise while aligning to shared company priorities. We work together and win together! The patient is waiting!

Relation is a committed equal opportunities employer and does not discriminate on the basis of gender, sexual orientation, marital or civil partnership status, gender re‑assignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age.