Senior Genomic Data Scientist - FTC, Adult Population Genomics Programme; offic

Company Description

Genomics England is a global leader in enabling genomic medicine and research, focused on creating a world where everyone benefits from genomic healthcare. Building on the 100,000 Genomes Project, we support the NHS’s world-first national whole genome sequencing service and run the growing National Genomic Research Library, alongside delivering numerous major genomics initiatives. By connecting research and clinical care at national scale, we enable immediate healthcare benefits and advances for the future.

Our mission is to provide the evidence and digital systems so that by 2035 genomics could play a role in up to half of all healthcare interactions, whilst securing the UK’s position as the best place to discover, prove and benefit from genomic innovations. We are accelerating our impact and working with patients, doctors, scientists, government and industry to improve genomic testing, and help researchers access the health data and technology they need to make new medical discoveries and create more effective, targeted medicines for everybody.

Behind the Healthcare and Research outcomes, Genomics England delivers through designing, developing and operating complex healthcare software systems. We're on the cusp of big changes with the real prospect of genomics becoming the fabric of everyday healthcare through the lifetime – from birth to old age.

We are hiring a Senior Genomic Data Scientist to join our newly established Adult Population Genomics Programme (APGP). This exciting initiative will sequence the genomes of 150,000 adults to better understand how genomics can support preventative healthcare, improve early disease detection, and enable more personalised and proactive interventions. A key element of the programme is the integration of pharmacogenomics, recognising its potential to support safer and more effective use of medicines across the population.

The Senior Genomic Data Scientist will lead the programme’s pharmacogenomics-focused analytical work. This includes evaluating technologies, benchmarking tools, and developing, validating, and implementing analysis workflows for the detection and reporting of pharmacogenomic variants. The person in this role will shape the analytical strategy and generate impactful insights from large-scale genomic and health data, helping the programme realise its potential for population-level precision medicine.

This role is based on a 2‑year fixed‑term contract.

• Contribute to study design and planning, in particular from statistics and evaluation perspective (e.g. power calculations, sample size calculations, outcomes modelling).
• Assess and benchmark technologies and bioinformatics tools for processing and analysis of whole genome data (e.g. alignment, variant callers, quality control), relevant genomic to pharmacogenomics and disease risk prediction in adults.
• Collaborate with Bioinformatic Engineers in development of data processing pipelines, including setting up the requirements, validation, testing, and impact assessment.
• Conduct custom computational analyses on whole genome sequencing datasets.
• Research the scientific literature, identify new approaches to genome analysis, and contribute to the publication and dissemination of our learnings in the form of scientific papers, white papers and conferences.

• Demonstrated experience in human germline DNA analysis in pharmacogenomics context, ideally with additional expertise in other areas such as rare disease genomics, polygenic risk prediction, population genetics, or complex genomic regions (e.g., HLA/KIR).
• Deep understanding and hands‑on experience of a broad range of bioinformatic techniques and approaches, especially related to whole genome sequencing, complex loci, haplotypes, and the tools and databases used for pharmacogenomics and human genome variant interpretation.
• Proficiency in programming, including working knowledge of python, and statistics, with experience in cloud‑scale or high‑performance computing, and understanding of experimental design, sample size, and power calculations.
• Proven experience…