Lead Genomic Data Scientist - Cancer; office locations

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 looking to hire a Lead Genomic Data Scientist to join our Bioinformatics Consulting team at Genomics England to lead on a range of cancer genome analysis and interpretation projects in collaboration with and on behalf of our external researchers and industrial partners.

The role of the Lead involves a harmonious blend of technical leadership and people management, with a primary focus on enhancing customized cancer genome analysis within our research environment.

Drawing upon a robust understanding of biomedical challenges and a commitment to producing high-quality code, the Lead Genomic Data Scientist plays a direct and influential role in crafting solutions and products. These outcomes are specifically designed to cater to the distinct requirements of our researchers and industrial collaborators, thereby contributing significantly to the advancement of our objectives.

Everyday responsibilities include:

• Proving technical and scientific leadership role in the realms of cancer genome analysis.
• Being the main point of contact for consulting collaborations, seamlessly communicating and planning with the relevant stakeholders.
• Actively contributing to the development, implementation, and continual enhancement of best practices for genome analysis at Genomics England.
• Spearheading end‑to‑end complex genomic analysis projects, involving aspects such as design, stakeholder engagement, code development, problem‑solving, reaching conclusions, and documentation.
• Conducting benchmarking exercises and enhancements for tools used in processing, analysis, and interpretation of whole genome data, encompassing alignment, variant calling, annotation, variant prioritization, interpretation, and quality control.
• Collaborating seamlessly with internal and external stakeholders to guarantee the successful delivery of projects.
• Employing and critically evaluating statistical genetics analysis methods to derive insights from large‑scale genomic data.
• Taking charge of managing and leading an inclusive, high‑performing team, ensuring the presence of the right skills to fulfil our mission.

Skills and Experience for Success:

• In-depth expertise in cancer genomics, understanding tumor drivers, and interpreting genomic data through targeted pathways.
• Proficient in utilizing Python for efficient data processing and analysis.
• Hands‑on experience in developing high‑quality and reusable code, with a strong command of Git and CI/CD practices.
• The capacity to thoughtfully evaluate statistical and/or machine learning techniques, and proficiently apply them in practical scenarios while interpreting results, considering the assumptions and limitations inherent in the methods.
• Experience in leading a cross‑functional analytical team in academic or industry environment.
• Ability to…