Senior Data Scientist - Computational Biology

<h2><strong>About Relation</strong></h2><p style="min-height:1.5em">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.</p><p style="min-height:1.5em">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.</p><p style="min-height:1.5em">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.</p><p style="min-height:1.5em">By joining Relation, you will help define how medicines are discovered and deliver meaningful impact for patients.</p><p style="min-height:1.5em"></p><h2>The opportunity</h2><p style="min-height:1.5em">We are seeking a Senior Data Scientist, Computational Biology to join Relation, working at the intersection of single-cell biology, spatial omics, and machine learning.</p><p style="min-height:1.5em">In this role, you will apply advanced computational and statistical approaches to analyse high-dimensional biological datasets, generating insights that directly inform disease understanding and drug discovery. You will sit within the Single Cell &amp; Spatial Omics function, working closely with ML researchers, experimental scientists, and software engineers to translate complex biological data into actionable knowledge.</p><p style="min-height:1.5em">This is a highly collaborative, scientifically driven role, suited to someone who enjoys working deeply with data, challenging models with biological insight, and contributing meaningfully to interdisciplinary research programmes.</p><p style="min-height:1.5em"></p><h2>Day to day, you will</h2><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Analyse and interpret single-cell, spatial, and other multi-omics datasets to uncover biological mechanisms relevant to disease and therapeutic intervention.</p></li><li><p style="min-height:1.5em">Develop and apply statistical and computational methods for transcriptomics and related omics data.</p></li><li><p style="min-height:1.5em">Use domain expertise to design rigorous evaluation tasks that test, challenge, and refine ML models.</p></li><li><p style="min-height:1.5em">Collaborate closely with ML scientists to inform model assumptions, features, and interpretation.</p></li><li><p style="min-height:1.5em">Work with experimental teams to help design experiments and validate computational hypotheses.</p></li><li><p style="min-height:1.5em">Clearly communicate insights, results, and methodologies to internal stakeholders and contribute to scientific publications.</p></li></ul><p style="min-height:1.5em"></p><h2>Professionally, you will have</h2><ul style="min-height:1.5em"><li><p style="min-height:1.5em">A PhD in computational biology, bioinformatics, statistics, physics, mathematics, or a related quantitative field.</p></li><li><p style="min-height:1.5em">Strong experience working with high-dimensional biological data, including transcriptomics and other omics modalities.</p></li><li><p style="min-height:1.5em">Proficiency in Python, with experience in scientific computing and data analysis.</p></li><li><p style="min-height:1.5em">A solid understanding of statistical modelling and quantitative methods applied to biological data.</p></li><li><p style="min-height:1.5em">Experience with Bayesian models.</p></li></ul><p style="min-height:1.5em"><u>Bonus experience</u></p><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Hands-on experience with single-cell and/or spatial omics data, including patient-derived samples.</p></li><li><p style="min-height:1.5em">Familiarity with machine learning approaches used in biological or biomedical research.</p></li><li><p style="min-height:1.5em">Experience working in interdisciplinary teams spanning biology, data science, and ML.</p></li><li><p style="min-height:1.5em">Exposure to scalable computing environments.</p></li></ul><p style="min-height:1.5em"></p><h2>Personally, you </h2><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Are comfortable working in a matrixed environment, <strong>balancing multiple stakeholders </strong>and contributing effectively across teams.</p></li><li><p style="min-height:1.5em">Take <strong>ownership of your work</strong>, proactively seek opportunities to contribute, and enable others to do their best work.</p></li><li><p style="min-height:1.5em"><strong>Communicate openly and directly</strong>, give and receive feedback constructively, and handle challenging conversations with respect.</p></li><li><p style="min-height:1.5em"><strong>Actively seek out diverse perspectives</strong>, build strong working relationships, and contribute to shared goals across teams.</p></li><li><p style="min-height:1.5em"><strong>Embrace challenges with openness and resilience</strong>, set high standards for yourself, and strive to deliver meaningful outcomes.</p></li></ul><p style="min-height:1.5em"></p><h2><strong>Working Style &amp; Culture at Relation</strong></h2><p style="min-height:1.5em">At Relation, we operate in a <strong>matrixed, interdisciplinary environment</strong>, 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!</p><p style="min-height:1.5em"></p><h2><strong>Recruitment Agencies</strong></h2><p style="min-height:1.5em">Please note that Relation <strong>does not accept</strong> 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.</p><p style="min-height:1.5em"><em>Relation is a committed equal opportunities employer.</em></p><p>Find <a href="https://www.arbeitnow.co.uk">Jobs in United Kingdom</a> on Arbeitnow</a>