Senior Data Scientist – Turing (LLMs, Agents, Data & Scientific Reasoning)

Department: Data Science/Computational Biology

Location: London

Employment Type: FullTime

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

Join the innovative Turing team, where we build computational systems that help scientists explore biological data, generate hypotheses, and reason about mechanisms of disease.

As a Senior Data Scientist, you will work at the intersection of computational biology, machine learning, and drug discovery, helping to build and apply computational approaches that support scientific interpretation and decision-making.

The Turing team sits at the intersection of machine learning, data science, and biology. We build systems that integrate diverse biomedical datasets, extract insights from the scientific literature, and support decision-making in target discovery and therapeutic development. Our work combines strong engineering, machine learning research, and deep engagement with disease biology.

This role is ideal for someone with a strong computational biology or drug discovery background who is excited by the opportunity to work closely with machine learning systems, including emerging AI approaches, in a highly applied scientific setting.

Day to day, you will

• Work with large, heterogeneous biomedical datasets, including omics, literature, knowledge bases, and other biological data sources, to generate insights relevant to target discovery and therapeutic development.

• Contribute to the interpretation of machine learning outputs in biological and drug discovery contexts.

• Collaborate closely with biologists, computational scientists, data scientists, and engineers to translate biological questions into computational analyses and practical tools.

• Prototype and productionise data pipelines, models, and analysis workflows that support ongoing discovery programmes.

• Work with large biological and pathway databases to support functional interpretation and knowledge discovery.

• Help develop and refine computational approaches that support reasoning over biological knowledge and evidence.

• Engage with modern AI methods, including LLM-based or agentic approaches where useful, as part of a broader scientific and computational toolkit.

Professionally, you will have

• A PhD or equivalent experience in computational biology, bioinformatics, machine learning, data science, or a related quantitative field.

• Strong programming skills in Python, with experience working with large-scale biological or biomedical datasets.

• A strong background in computational biology, bioinformatics, or drug discovery, with the ability to work effectively on biologically grounded problems.

• Experience interpreting complex analytical or machine learning outputs in a scientific context.

• Experience building robust analytical workflows, data pipelines, or production-facing computational tools.

• Comfort working across interdisciplinary teams in environments where biology, machine learning, and engineering intersect.

• An interest in modern AI approaches, including LLMs and related methods, and how they can support scientific discovery.

Bonus experience

• Experience working with large biological, pathway, or functional interpretation databases.

• Experience in pharmaceutical, biotech, or applied drug discovery settings.

• Experience across multiple biological data modalities, such as transcriptomics, proteomics, epigenomics, or related areas.

• Experience applying machine learning or AI methods to biomedical or scientific problems.

• Familiarity with scientific literature mining, knowledge integration, or knowledge representation.

• Experience working in highly cross-functional teams combining biology, machine learning, and 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.