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

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 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. DAY TO DAY, YOU WILL - 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. PROFESSIONALLY, YOU WILL HAVE - 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. Bonus experience - 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. 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.