Data Scientist

Genomics is a science-led transatlantic TechBio combining large-scale genetic and health data with proprietary analytics to accelerate drug discovery and advance predictive, preventative healthcare. We are united by a single vision to help people live longer healthier lives, using the power of genomics.

Genomics aims to help people live longer, healthier lives in two ways: super-charging drug discovery and development for novel treatments with our AI-enabled advanced genetic analytics platform, and by helping people understand their personal risk of common chronic diseases through polygenic risk scores - giving doctors and health systems the chance to get the right people into the right prevention, screening and treatment programmes at the right time.

We're looking for an exceptional Data Scientist with a strong background in human genetics and genomics, and advanced skills in data science, statistics and computational analysis. You might be a great fit for this role if you're a methods-oriented domain specialist within the broad field of genomics with some exposure to software engineering practices and an interest in developing that side of your skillset. The primary purpose of the role is to develop and integrate support for processing, quality control and analysis of new types of data into our production and research software tools.

You'll join a team of experts in human genetics, data science and software engineering, building the platform at the heart of our Life Sciences work – helping us derive new insights into human biology and guide drug development towards safer, more effective targets. How your time splits across data processing workflows, statistical methods and software engineering will reflect your own balance of scientific and computational strengths, with an emphasis on genetics domain expertise and data analysis, including processing and interpreting functional genomics data.

This role can be hired at IC2 (Data Scientist) or IC3 (Senior Data Scientist) level, depending on your experience. At IC3, you'll operate with greater autonomy, hold a broader scientific scope, bring deeper subject-matter expertise, and lead analyses that integrate multiple genomic data sources, working with cross-disciplinary teams to deliver value.

At the heart of this role is the opportunity to expand and improve how we use data and cutting edge methods to identify and validate effective and safe drug targets via deeper understanding of disease mechanisms.

• Identify innovative uses of new types of data for integration into our data and analytics platform. E.g from functional genomics and perturbation screens, molecular profiling and expression atlases, genomic and functional annotations, and curated interaction, pathway and ontology resources.

• Implement production quality code for processing, transforming and quality control of new data types for integration into our larger data model

• Contribute to and implement statistical and machine learning methods to a high standard of robustness, validation and reproducibility.

• Contribute to internal and external presentations and publications arising from our work.

• Keep your knowledge current on innovation and good practice in genomics, functional genomics and statistical genetics.

• At Senior (IC3) level, you'll also lead projects that integrate multiple functional genomics and genetic data sources, coordinating with cross-disciplinary teams to deliver value.

• Strong knowledge of human genetics and functional or clinical genomics, and the ability to apply it to research questions.

• Skilled at analysing and learning from large-scale biological datasets, including statistical and machine learning methods.

• Experienced processing and interpreting data from functional genomics, molecular and expression atlases, genomic annotations, and curated pathway and interaction resources, including quality control.

• Competent writing code in Python and/or R for data analysis, with an appreciation of good software development practice.

• Comfortable using LLM programming assistants appropriately within a research analysis environment.

• Experienced running tools and workflows in a scalable system, for example Linux based HPC environments or on cloud systems.

• Experience working on a collaborative codebase using version control and CI/CD.

• Experience working in remote, cloud-based environments, e.g. AWS.

• Prior experience working in a team, ideally in an industry setting.

• A PhD or postgraduate degree in genetics, genomics, computational biology or bioinformatics, or statistics and machine learning applied in these fields.

We are committed to providing a transparent, supportive, and rewarding work environment.