Genomic Data Scientist; office locations

Position: Genomic Data Scientist (we have office locations  amp )
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.

Job Description

We are seeking a Genomic Data Scientist to join our Bioinformatics Consulting team to work 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 work as part of multidisciplinary teams to develop and execute cutting edge projects that leverage Genomics England datasets to address research goals such as drug target identification, biomarker discovery, diagnostic discovery, and patient stratification.

You will contribute to the scoping, implementation, and application of state-of-the-art approaches for analysis of genomic and other omics modalities, in both leading and supporting capacity. As an expert user of our datasets and research environment, you will develop and fine-tune tools and pipelines to perform custom computational analyses, generate new data and contribute to high quality reports and documentation.

Everyday responsibilities include:

Preparing data for downstream analysis, e.g. through quality control, functional annotation, aggregation, harmonisation across different datasets.
Planning and supporting analyses to meet project objectives with internal teams and external stakeholders. Providing support to internal teams and collaborators and being the point of reference for genomic datasets and analytical approaches.
Performing custom computational analyses on whole genome sequencing and other omics data, such as GWAS, aggregate variant testing, meta-analysis, differential abundance, fine-mapping and MR.
Researching the scientific literature, identifying new approaches to processing and analysis of genomics and multi-omics data, benchmarking and improving tools.
Contributing to the publication and dissemination of findings via scientific papers, white papers and conference presentations. Skills and experience for success:

Strong programming skills (R, Python) and solid background of statistical genetics.
Demonstrable experience using whole genome sequencing data in the context of human genetics.
Strong background in human disease genetics, preferably in rare or complex disease, demonstrated by publication record or industry track record. 
Demonstrable experience in working with long read sequencing data (preferred) or other omics modalities.
Proven track record in one or more areas of human germline DNA analysis such as genetic association testing, population genetics, pharmacogenomics, rare disease genomics, structural variation analysis, working with complex genomic regions such as HLA/KIR/PGx. 

Experience with working in the cloud, building containers, and running pipelines using workflow languages (ideally Nextflow).
Proven ability to…