Data Scientist – Single Cell & Spatial (12-month FTC)

About Relation

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.

We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does not discriminate on the basis of gender, sexual orientation, marital or civil partnership status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age.

By joining Relation, you will help define how medicines are discovered and deliver meaningful impact for patients.

The opportunity

This is a unique opportunity for a data scientist to work on multi-omics data to drive transformative insights into drug discovery. As a member of the Cross Indication team, you will contribute to identifying and validating drug targets through advanced data analysis and innovative computational approaches.

The Cross Indication team collaborates across both Relations internal and partnership programmes, applying state-of-the-art computational methods to integrate diverse datasets. By combining biological insights with advanced data analytics, the team drives target discovery and validation initiative.

Day to day, you will

• Develop and implement robust computational workflows for the integration and analysis of multi-omics datasets, including single-cell and/or spatial modalities.

• Design and apply statistical and computational models for analysing transcriptomics and related omics data.

• Use biological insight and data intuition to design meaningful, challenging evaluation tasks for ML models.

• Collaborate closely with ML researchers to inform and iterate on model architectures and assumptions.

• Partner with experimental scientists to help formulate, test, and validate computational hypotheses.

• Communicate findings clearly through internal presentations and contribute to scientific publications.

Professionally, you will have

• A PhD in computational biology, bioinformatics, statistics, physics, mathematics, or a related quantitative discipline.

• Strong experience analysing high-dimensional biological data, including transcriptomics and other omics datasets.

• Proficiency in Python, with experience working in high-performance or cloud computing environments.

Bonus experience

• Experience with single-cell and/or spatial omics data, including patient-derived datasets.

• Familiarity with machine-learning approaches applied to biological data.

• A solid grounding in statistical modelling, algorithm development, or data integration methods.

• Experience working effectively within highly interdisciplinary teams spanning biology, ML, and software engineering.

Personally, you

• Are comfortable working in a matrixed environment, balancing multiple stakeholders and contributing effectively across teams.

• Take ownership of your work, proactively seek opportunities to contribute, and enable others to do their best work.

• Communicate openly and directly, give and receive feedback constructively, and handle challenging conversations with respect.

• Actively seek out diverse perspectives, build strong working relationships, and contribute to shared goals across teams.

• Embrace challenges with openness and resilience, set high standards for yourself, and strive 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!

Recruitment Agencies

Please note that Relation does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation will not be liable for any fees associated with unsolicited CVs.

Relation is a committed equal opportunities employer.