Senior Genomics Data Scientist

We are seeking a Senior Genomics Data Scientist to join our Bioinformatics Consulting team at Genomics England and lead on a range of genome analysis and interpretation projects with an emphasis in rare or complex disease, in collaboration with and on behalf of our external researchers and industrial partners.

In this role, you will develop and execute cutting edge statistical and computational genomics analyses that leverage Genomics England datasets to address a broad set of research questions.

You will drive projects from conception to completion and lead the scoping and implementation of state-of-the-art statistical and computational approaches for analysis of genomic and other omics modalities. You will develop and fine-tune tools and pipelines to carry out custom analyses on demand in our research environment, generate new data and disseminate findings in publication-quality reports and documentation.

Everyday responsibilities include:

• Performing custom computational analyses on whole genome sequencing and other omics datasets, including genome-wide association studies, aggregate variant association testing, meta-analysis, transcriptome-wide association studies, fine-mapping and MR.
• Preparing statements of work for projects and delivery of publication-level quality reports of the findings and analyses, with minimal supervision.
• Preparation of data for downstream analysis, e.g. through quality control, functional annotation, harmonisation across different datasets.
• Researching the scientific literature, identifying and implementing new approaches to genome analysis, as well as contributing to the publication and dissemination of our learnings in the form of scientific papers, white papers and conferences.
• Providing computational genetics expertise to utilise the right tools for each analyses and support internal teams and commercial clients, being the point of reference for genomic datasets and analytical approaches.
• Benchmarking and improving tools for processing and analysis of whole genome sequencing data.

Skills and Experience for Success

We anticipate the ideal candidate will have:

• Strong programming skills (R, Python) and demonstrable knowledge of statistical genetics.
• Demonstrable experience in using next generation sequencing data at scale in the context of human genetics.
• Strong background in human disease genetics, preferably in rare or complex disease, demonstrated by leading high impact publications or industry track record.
• Demonstrable experience in one or more areas of human germline DNA analysis such as genetic association testing, population genetics, pharmacogenomics, rare disease genomics, risk score prediction, structural variation analysis, working with complex genomic regions such as HLA/KIR.
• Experience with working in the cloud, building containers, and running pipelines in nextflow.
• Proven ability to communicate with stakeholders from diverse backgrounds (e.g. management, IT, R&D, biology, bioinformatics) and a clear understanding of clinical and phenotypic data management and the sensitivities surrounding patient cohort data.
• Excellent interpersonal skills, keeping track of customer relationships, providing high calibre troubleshooting, identifying unmet customer needs and suggesting solutions to improve material or analytical approaches.

Requirements

A PhD in Computational or Statistical Genetics with extensive post-doctoral or equivalent work experience in human genetics research.