Senior Data Scientist - Computational Biology

Relation Therapeutics

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 Relation is offering an outstanding opportunity for a Data Scientist/Senior Scientist to support and shape statistical and population genomics efforts to accelerate target identification and validation across multiple therapeutic areas. You will work with large-scale human genetics resources (e.g. biobanks and population cohorts), internally generated data, and apply cutting-edge statistical genetics methodologies to generate actionable insights. You will operate at the interface of human genetics, computational biology, and machine learning, translating genetic evidence and multi-omics into target prioritisation frameworks and mechanistic hypotheses. You will play a key role in developing robust, scalable analysis pipelines and ensuring genetic insights are integrated into decision-making across the organisation. Day to day you will, * Perform statistical and population genomics analyses using large-scale datasets to support target discovery and validation. * Design and implement statistical genetics methodologies for target prioritisation, including approaches leveraging GWAS, fine-mapping, colocalisation, MR, polygenic risk, rare variant analyses, and functional annotation. * Develop scalable computational workflows for reproducible genetics analysis, enabling robust and efficient delivery across multiple programmes. * Integrate human genetics evidence with multi-omics datasets (e.g. transcriptomics, proteomics) to uncover disease mechanisms and prioritise actionable targets. * Partner closely with experimental, translational, and ML teams to validate hypotheses, interpret findings, and guide downstream decision-making. * Communicate results clearly and confidently to internal stakeholders, including presenting methods, results, risks/limitations, and recommendations. * Contribute to publications, scientific communications, and project documentation, supporting scientific excellence and external visibility. Professionally, you will have, * PhD in statistical genetics, genomics, computational biology, bioinformatics, or a related quantitative field. * Post-PhD experience is desiderable, ideally including time in an industry, biotech, or pharmaceutical environment. * Deep expertise in statistical genetics and population genomics, including experience with large-scale human genetic datasets and post-GWAS analyses. * High proficiency in Python (preferred) and R, with experience working in high-performance computing environments. * Ability to operate independently, providing technical expertise and driving projects from concept through delivery. * Bonus experience: * Familiarity with single-cell transcriptomics or patient-derived datasets. * Experience working in interdisciplinary teams within biotech or pharma settings. * Knowledge of machine learning techniques applied to biological data. * Understanding of the end-to-end drug discovery process and how genetic evidence informs decision-making. 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.

Relation Therapeutics

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 senior data scientist to work on DNA sequence modelling, statistical machine learning, and functional genomics in support of target discovery and mechanism elucidation. You will develop and apply computational models that connect genetic variation and regulatory DNA sequence to downstream molecular phenotypes, cellular programmes, and disease biology. Embedded within the Rosalind team you will build and evaluate models that link sequence to function - including variant effect prediction,regulatory activity modelling and representation learning for genomic data. DAY TO DAY YOU WILL: * Develop and implement machine learning models for DNA sequence, regulatory elements, and genetic variation in disease-relevant contexts. * Build, evaluate and benchmark models for sequence-to-function tasks such as variant effect prediction, regulatory activity prediction, and the interpretation of non-coding disease signals. * Integrate sequence-derived representations with transcriptomic, epigenomic, and perturbational datasets to uncover disease mechanisms and support target prioritisation. * Partner closely with experimental and machine learning researchers to validate hypotheses, interpret results, and guide downstream studies. * Communicate findings clearly to internal stakeholders, including presenting methods, results, and recommendations. * Contribute to publications, scientific communications, and project documentation, supporting scientific excellence and external visibility. PROFESSIONALLY, YOU WILL HAVE * PhD in computational biology, machine learning, statistics, genomics, bioinformatics, or a related quantitative discipline. * Post-PhD experience, ideally including time in an industry, biotech, or pharmaceutical environment. * Experience with DNA language models, genomic foundation models, or transformer-based sequence models. * Understanding of statistical machine learning and probabilistic modelling, with experience selecting and evaluating appropriate modelling approaches for complex biological datasets. * Knowledge of statistical genetics methods (e.g fine-mapping, colocalisation,, or variant to gene approaches). * High proficiency in Python (preferred) and R, with experience working in high-performance computing environments. * Ability to operate independently, driving projects from concept through delivery. * Bonus experience: * Familiarity with single-cell transcriptomics or patient-derived datasets. * Experience working in interdisciplinary teams within biotech or pharma settings. * Experience integrating machine learning models with genomics, single-cell, or perturbation datasets. * Familiarity with 3D genome / chromatin interaction data where relevant (Hi-C, Capture-C, etc.). 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.

Relation Therapeutics

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 Relation is offering an outstanding opportunity for an Senior Scientist, Biologics Drug Discovery to bring deep biologics drug discovery knowledge to our growing pipeline. You will contribute to target assessment, modality selection and biologics discovery strategies through deep technical expertise and hands-on scientific execution from early concept through to IND-enabling studies. As Relation grows its scientific and machine learning capabilities, you will act as a highly experienced scientist, bringing deep expertise in antibody discovery and engineering while contributing directly to programme execution and scientific decision-making, working alongside our computational, ML, and translational teams to translate biological insight into well-designed molecules with a credible path to the clinic. We are particularly interested in scientists who have personally designed, engineered and optimised antibody molecules, including experience with affinity maturation, CDR engineering, developability assessment and data-driven molecule optimisation. You will additionally be a key technical voice in pipeline decisions and a trusted partner to colleagues across Drug Discovery and beyond.   DAY TO DAY, YOU WILL * Demonstrated hands-on experience designing, engineering and optimising antibody molecules, with a strong understanding of the experimental approaches used to assess potency, selectivity, developability and mechanism of action. * Ability to independently interpret complex datasets and use those data to drive molecule design and optimisation decisions. * Maintain a hands-on role in biologics discovery activities while partnering closely with internal and external teams. * Drive biologics programs end-to-end — from target validation and hit identification through lead characterization, optimization, and developability triage — against agreed Target Product Profiles (TPPs). * Make informed modality decisions across the biologics landscape (antibodies, bispecifics, ADCs, fusion proteins, fragments) and ensure the right molecule is selected for the right target and indication. * Design and oversee fit-for-purpose discovery packages, combining cell-based functional assays, biophysical characterization (SPR/Biacore, BLI/Octet), and developability assessment to drive sound candidate selection. * Operate effectively in a matrixed pharma/biotech environment, partnering with Computational Biology, Machine Learning, CMC, DMPK, Toxicology, and Translational colleagues to de-risk candidates and progress them toward IND-enabling studies. * Partner with external collaborators and CROs, contributing to study design, data review and scientific interpretation. * Share expertise with colleagues and contribute to a collaborative scientific environment. * Partner with our ML and computational biology teams to bring biologics drug discovery insight into how predictive and generative approaches are applied to target selection, molecule design, and lead optimization. * Personally contribute to the design, engineering and optimisation of antibody molecules, using experimental data to guide scientific decisions and progression strategies. * Contribute to Relation’s scientific culture by mentoring junior scientists in biologics drug discovery, supporting publications and conference visibility, and helping to shape the broader scientific identity of the biologics group.   PROFESSIONALLY, YOU WILL HAVE * A PhD. in Molecular Biology, Immunology, Pharmacology, Cell Biology, Protein Engineering, or a related life-science discipline. * Hands-on drug discovery experience gained in a pharma or biotech setting, with a clear track record of contributing to biologics programs progressing through key discovery milestones (target validation, hit-to-lead, lead optimization, candidate selection). * Proven experience working in a matrixed pharma/biotech environment, partnering effectively across functions (e.g. CMC, DMPK, Toxicology, Computational/ML, Translational) and balancing multiple stakeholders. * Deep working knowledge of biologics drug discovery: how biology is translated into a molecule, how modalities are chosen, how discovery cascades are designed, and what data are needed at each stage to make sound progression decisions. * Familiarity with the biologics modality landscape (antibodies, bispecifics, ADCs, fusion proteins, fragments) and an informed view of when each modality is the right tool for the biology. * Hands-on experience with the data types that drive biologics drug discovery decisions, including cell-based functional and screening assays and biophysical characterization (SPR/Biacore, BLI/Octet). * Working experience of CRO management across biologics drug discovery activities (e.g. molecule production, in vitro pharmacology, in vivo studies). * A good understanding of biologics drug discovery end-to-end, including TPP-driven decision-making, developability considerations, and awareness of what is required to support IND-enabling activities. * Curiosity about how ML and computational approaches can complement traditional biologics discovery workflows, and an interest in shaping how those tools are deployed. Bonus experience: * Familiarity with bone biology and bone-microenvironment models (osteoblast, osteoclast, osteocyte; mineral-binding or resorption assays). * Peer-reviewed publications in the biologics drug discovery space, prior experience mentoring junior scientists, and exposure to a TechBio or computationally-driven discovery environment are also welcome.   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.