Lead Genomics Data Scientist

Canary Wharf
3 months ago
Applications closed

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Lead Data Scientist

Company Description

Genomics England partners with the NHS to provide whole genome sequencing diagnostics. We also equip researchers to find the causes of disease and develop new treatments – with patients and participants at the heart of it all.

Our mission is to continue refining, scaling, and evolving our ability to enable others to deliver genomic healthcare and conduct genomic research.

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.

Job Description

We are looking to hire a Lead Genomic Data Scientist to join our Bioinformatics Consulting team at Genomics England and 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.  
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.  
Ensuring the adherence to high standards of relevance, excellence, and clinical safety in genomic analysis, aligning with Genomics England accreditation requirements.  
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

Qualifications

PhD degree or equivalent practical experience in an industry setting.

Additional Information

Salary from £71,000

Please note for this role there is a requirement to be in our Canary Wharf office minimum 2 times per week.

Being an integral part of such a meaningful mission is extremely rewarding in itself, but in order to support our people, we’re continually improving our benefits package. We pride ourselves on investing in our people and supporting them to achieve their career goals, as well as offering a benefits package including: 

Generous Leave: 30 days’ holiday plus bank holidays, additional leave for long service, and the option to apply for up to 30 days of remote working abroad annually (approval required).
Family-Friendly: Blended working arrangements, flexible working, enhanced maternity, paternity and shared parental leave benefits.
Pension & Financial: Defined contribution pension (Genomics England double-matches up to 10%, however you can contribute more if you wish), Life Assurance (3x salary), and a Give As You Earn scheme.
Learning & Development: Individual learning budgets, support for training and certifications, and reimbursement for one annual professional subscription (approval required).
Recognition & Rewards: Employee recognition programme and referral scheme.
Health & Wellbeing: Subsidised gym membership, a free Headspace account, and access to an Employee Assistance Programme, eye tests, flu jabs.Genomics England is actively committed to providing and supporting an inclusive environment that promotes equity, diversity and inclusion best practice both within our community and in any other area where we have influence. We are proud of our diverse community where everyone can come to work and feel welcomed and treated with respect regardless of any disability, ethnicity, gender, gender identity, religion, sexual orientation, or social background.

Genomics England’s policies of non-discrimination and equity and will be applied fairly to all people, regardless of age, disability, gender identity or reassignment, marital or civil partnership status, being pregnant or recently becoming a parent, race, religion or beliefs, sex or sexual orientation, length of service, whether full or part-time or employed under a permanent or a fixed-term contract or any other relevant factor. 

Genomics England does not tolerate any form of discrimination, harassment, victimisation or bullying at work. Such behaviour is contrary to

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