Scientist

Posted 20 Days Ago
Be an Early Applicant
Triangle Trailer Park, Township of Jacksonville, NC, USA
In-Office
Entry level
Biotech
The Role
Conduct statistical and computational analyses of genomic and health data to support therapeutic target discovery, validation, and patient stratification. Generate disease and treatment hypotheses using statistical genetics, AI/ML, and causal inference approaches. Develop polygenic risk and other predictive tools, analyze omic and electronic health record data, build reproducible pipelines, and communicate scientific findings to internal and external stakeholders.
Summary Generated by Built In

Location: Hybrid from our RTP office

 

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 top-of-market 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

  • PTO: 25 days vacation, plus 8 federal holidays, plus an extra 3-day company-wide shutdown at year-end.

  • Full Coverage: 401k, Comprehensive Health, Dental, and Vision plans, Health Savings Account (HSA), Life/AD&D, and Disability coverage.

 
Work Environment & Culture
  • Flexible Working: Hybrid Working.(e.g. From our RTP 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.

     

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.

 
 
 

Skills Required

  • Strong foundation in statistics, including modeling and regression
  • Strong foundation in genetics and molecular biology
  • Statistical programming experience using Python or R
  • Experience with statistical genetics approaches such as GWAS, colocalization, fine-mapping, Mendelian randomization, or polygenic risk scores
  • Experience defining phenotypes from electronic health records
  • Knowledge of Bayesian inference, high-dimensional statistics, and causal inference
  • Experience with software engineering practices, including Git, GitHub, testing, documentation, agentic coding, and containerization
  • Experience building and running reproducible pipelines using WDL, Snakemake, or Nextflow
  • Experience with cloud computing and trusted research environments such as DNAnexus or Verily Workbench
  • Experience developing methods in statistical genetics
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The Company
HQ: Oxford
164 Employees
Year Founded: 2014

What We Do

We are a pioneering healthcare company that aims to transform health through the power of genomics. The company was formed in 2014 by four world-leading statistical and human geneticists at the University of Oxford, including Professor Sir Peter Donnelly and Professor Gil McVean. We use large-scale genetic information to realise preventative medicine and improve drug discovery. We're a world-leader in genomic prevention: a paradigm-changing approach to sustainable healthcare which for the first time allows reliable, personalised estimates of risk for all the common diseases and cancers, well ahead of disease manifestation, allowing accurate and early interventions and tailored screening. Our proprietary algorithms and databases offer something no competitor can: the ability to accurately link minute variation across the entire genome to changes in thousands of biological measurements and disease outcomes, to generate population-level insights for healthcare systems, individual-level insights for clinicians about the risk of common diseases, and new understanding of disease processes. In August 2018, we announced a multi-year collaboration with Vertex to use human genetics and data science to advance discovery of precision medicines. We also have several pilot programmes in development within UK and US healthcare systems. Our team is a multi-disciplinary group focused on finding powerful and creative solutions for bringing subject-leading science to as wide an audience as possible, and, in doing so, offer the chance of transforming lives around the world. The workforce is highly qualified and consists of over 150 people, including genomic scientists, computational biologists, statisticians, software engineers, product developers, data scientists and commercial strategists. We are headquartered in Oxford, with offices in Cambridge (UK), London (UK), and Boston (US).

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