Values

The ad says“Experience with software engineering practices (version control [Git & GitHub], testing, documentation, agentic coding, containerisation)”
The ad says“Knowledge of Bayesian inference, high dimensional statistics, causal inference.”
The ad says“Knowledge of Bayesian inference, high dimensional statistics, causal inference.”
The ad says“Experience using cloud computing and trusted research environments e.g. DNAnexus or Verily Workbench.”
The ad says“Experience using a broad array of statistical genetics approaches (e.g., GWAS, colocalization, fine-mapping, Mendelian randomization, polygenic risk scores)”
The ad says“Experience with software engineering practices (version control [Git & GitHub], testing, documentation, agentic coding, containerisation)”
The ad says“Experience using cloud computing and trusted research environments e.g. DNAnexus or Verily Workbench.”
The ad says“Experience with software engineering practices (version control [Git & GitHub], testing, documentation, agentic coding, containerisation)”
The ad says“Experience using a broad array of statistical genetics approaches (e.g., GWAS, colocalization, fine-mapping, Mendelian randomization, polygenic risk scores)”
The ad says“Experience with software engineering practices (version control [Git & GitHub], testing, documentation, agentic coding, containerisation)”
The ad says“Experience with software engineering practices (version control [Git & GitHub], testing, documentation, agentic coding, containerisation)”
The ad says“Experience using a broad array of statistical genetics approaches (e.g., GWAS, colocalization, fine-mapping, Mendelian randomization, polygenic risk scores)”
The ad says“Knowledge of Bayesian inference, high dimensional statistics, causal inference.”
The ad says“Experience using a broad array of statistical genetics approaches (e.g., GWAS, colocalization, fine-mapping, Mendelian randomization, polygenic risk scores)”
The ad says“Experience with methods development within statistical genetics”
The ad says“Experience building and running reproducible pipelines e.g., using WDL, Snakemake, or NextFlow.”
The ad says“Experience defining phenotypes from electronic health records.”
The ad says“Experience using a broad array of statistical genetics approaches (e.g., GWAS, colocalization, fine-mapping, Mendelian randomization, polygenic risk scores)”
The ad says“Experience building and running reproducible pipelines e.g., using WDL, Snakemake, or NextFlow.”
The ad says“Experience building and running reproducible pipelines e.g., using WDL, Snakemake, or NextFlow.”
The ad says“Experience with software engineering practices (version control [Git & GitHub], testing, documentation, agentic coding, containerisation)”
The ad says“Experience with software engineering practices (version control [Git & GitHub], testing, documentation, agentic coding, containerisation)”
The ad says“Experience using cloud computing and trusted research environments e.g. DNAnexus or Verily Workbench.”
The ad says“Experience with software engineering practices (version control [Git & GitHub], testing, documentation, agentic coding, containerisation)”
The ad says“Experience building and running reproducible pipelines e.g., using WDL, Snakemake, or NextFlow.”

Location: Oxford or London (Hybrid)

The Mission: Why We Exist

Genomics is a science-led transatlantic TechBio combining large-scale genetic and health data with proprietary analytics to accelerate drug discovery and advance predictive, preventative healthcare. We are united by a single vision to help people live longer healthier lives, using the power of genomics.

Genomics aims to help people live longer, healthier lives in two ways: super-charging drug discovery and development for novel treatments with our AI-enabled advanced genetic analytics platform, and by helping people understand their personal risk of common chronic diseases through polygenic risk scores - giving doctors and health systems the chance to get the right people into the right prevention, screening and treatment programmes at the right time.

A Day in the Life

At Genomics, we tackle major scientific challenges in harnessing genomic data to improve human health.

This role is part of the Life Sciences team, working on a range of challenges spanning the therapeutic development cycle – including discovering and validating therapeutic targets and developing patient stratification strategies. The Scientist is an early-career member of the team, who will thrive in a highly collaborative team environment. With the team’s support, you will develop and execute innovative and rigorous scientific approaches, and will effectively communicate findings to both internal and external stakeholders.

For example, a Scientist may:

Generate novel therapeutic hypothesis for diseases with unmet need, mining the in-house data resources using statistical approaches to understand the causal pathophysiology of disease, identify and triage potential targets with genetic evidence, and build a rich understanding of the cell types, cellular function, tissue-level characteristics, patient populations and biomarkers needed to support a development program.
Apply and optimise risk tools for patient stratification that combine genetic information (through polygenic risk scores) with conventional risk factors, to find those individuals most at risk of disease onset or progression and those most likely to benefit from particular therapies.

To be successful in this role, you will: bring a strong foundation in the application of statistical and computational techniques in biomedical science that you can apply in innovative ways, thrive on analysing vast and diverse sources of ‘omic data using leading statistical or AI/ML approaches to make meaningful insights into complex problems, and take pride in effectively sharing your findings with others.

Who You Are

Must have, solid foundations in:

Statistics (modelling, regression)
Genetics and molecular biology
Statistical programming (e.g., Python or R)

Preferred:

Experience using a broad array of statistical genetics approaches (e.g., GWAS, colocalization, fine-mapping, Mendelian randomization, polygenic risk scores)
Experience defining phenotypes from electronic health records.
Knowledge of Bayesian inference, high dimensional statistics, causal inference.
Experience with software engineering practices (version control [Git & GitHub], testing, documentation, agentic coding, containerisation)
Experience building and running reproducible pipelines e.g., using WDL, Snakemake, or NextFlow.
Experience using cloud computing and trusted research environments e.g. DNAnexus or Verily Workbench.
Experience with methods development within statistical genetics

Your Package

We are committed to providing a transparent, supportive, and rewarding work environment.

Compensation & Growth

Competitive Salary: Salaries are externally benchmarked annually to ensure competitive compensation.
Clear Career Path: A straightforward, open progression framework means you'll always know the path to promotion and how to achieve your next career goal.
Continuous Learning: Including external courses and a wide library of L&D materials, because your growth is our success.

Wellbeing & Time Off

Holiday: 25 days annual leave, plus bank holidays, plus an extra 3-day company-wide shutdown at year-end.
Financial & Health Security: Robust benefits including a market-leading pension scheme, comprehensive private health insurance for you and your family with NO excess, critical illness, and life assurance.
Enhanced Leave: Enhanced paid family leave to support all new parents.

Work Environment & Culture

Flexible Working: Hybrid Working (e.g., From our London, Oxford Office)
Truly Inclusive Time Off: Our 'Bank Your Bank Holiday' program allows you to exchange public holidays for dates that hold personal or cultural significance to you.
Vibrant Social Culture: From regular Town Halls and team picnics to organised sports events, our social committee ensures frequent opportunities to connect and celebrate.
Green Commute: Cycle-to-Work scheme and convenient office locations near major transport hubs.

Ready to Build the Future?

If this opportunity excites you, apply now!

We are dedicated to creating a diverse environment and are proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Genomics politely requests no contact from recruitment agencies. We do not accept speculative CVs from recruitment agencies nor accept the fees associated with them.

Asks for

Values

Compensation & Growth

Wellbeing & Time Off

Work Environment & Culture