Relation Therapeutics
Snr/Principal Data Scientist – Turing (LLMs, Agents, Data & Scientific Reasoning)
🇬🇧London, England, United Kingdom2 months ago
SeniorFull TimeEN
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.
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 / Principal Data Scientist, you will develop and apply modern AI approaches, including large language models, agentic workflows, and data-driven evaluation systems, to accelerate scientific discovery.
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 excited about applying LLMs and agent-based systems to complex scientific problems, working closely with biologists, data scientists, and engineers to turn computational ideas into practical tools for discovery.
Develop and deploy LLM-driven systems to support scientific discovery, including literature analysis, hypothesis generation, and knowledge extraction.
Design and implement agentic workflows that integrate multiple tools, models, and data sources to support biological reasoning and research workflows.
Work with large, heterogeneous biomedical datasets (omics, literature, knowledge bases, and clinical data) to generate insights relevant to target discovery.
Develop evaluation frameworks and benchmarks to assess the performance and reliability of AI systems in scientific contexts.
Collaborate closely with biologists, computational scientists, and engineers to translate biological questions into computational solutions.
Prototype and productionise data pipelines, models, and analysis workflows that support ongoing discovery programmes.
Contribute to the development of new computational approaches for reasoning over biological knowledge and evidence.
A PhD or equivalent experience in computational biology, machine learning, data science, or a related quantitative field.
Strong practical experience working with large language models and modern AI tooling, including prompt engineering, tool use, retrieval systems, or agent-based architectures.
Strong programming skills in Python, with experience working with large-scale datasets and modern ML tooling.
Experience designing evaluation frameworks, benchmarks, or testing methodologies for machine learning systems.
An understanding of biological data and the drug discovery process, or a strong motivation to work in this domain.
Experience applying LLMs or AI systems to scientific or biomedical data.
Familiarity with literature mining, knowledge integration, or scientific knowledge representation.
Experience building multi-step or agent-based reasoning systems.
A background in computational biology, genomics, or drug discovery.
Experience working in cross-disciplinary teams combining machine learning and biology.
A collaborative team player who enjoys working in interdisciplinary environments.
A clear communicator who can translate complex ideas across computational and biological teams.
Curious, pragmatic, and motivated by solving meaningful scientific problems.
Excited to work on technology that can have real impact on patients.
Humble, thoughtful, and eager to learn.
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!
Relation Therapeutics is a committed equal opportunities employer.
RECRUITMENT AGENCIES: Please note that Relation Therapeutics does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation Therapeutics will not be liable for any fees associated with unsolicited CVs.