Hybrid Cancer Genomics Lead Data Scientist

Hybrid Cancer Genomics Lead Data Scientist

Full-Time 60000 - 80000 Β£ / year (est.) No working from home possible
Genomics England

At a Glance

  • Tasks: Lead cancer genome analysis projects and collaborate with researchers and industry partners.
  • Company: Genomics England, a leader in bioinformatics and genomic research.
  • Benefits: Competitive salary, flexible working, and opportunities for professional growth.
  • Other info: Join a dynamic team focused on impactful genomic research.
  • Why this job: Make a real difference in cancer research while leading innovative data science projects.
  • Qualifications: PhD or equivalent experience in data science, with strong Python skills.

The predicted salary is between 60000 - 80000 Β£ per year.

Genomics England invites a Lead Genomic Data Scientist to join our Bioinformatics Consulting team.

You will lead cancer genome analysis and interpretation projects in collaboration with external researchers and industrial partners, blending technical leadership with people management.

With Ph D or equivalent practical experience, you will apply Python-based data processing, robust coding and CI/CD practices, and present results to diverse audiences.

#J-18808-Ljbffr

Hybrid Cancer Genomics Lead Data Scientist employer: Genomics England

Genomics England is an exceptional employer, offering a dynamic and inclusive work environment in the heart of Cambridge, Leeds, or London. With generous leave policies, flexible working arrangements, and a strong commitment to employee development, we empower our Genomic Data Scientists to thrive both personally and professionally while contributing to groundbreaking cancer research. Our focus on diversity and well-being ensures that every team member feels valued and supported in their journey.

Genomics England

Contact Details:

Genomics England Recruitment Team

We think you need these skills to ace Hybrid Cancer Genomics Lead Data Scientist

Genomic Data Analysis
Bioinformatics
Python Programming
Data Processing
CI/CD Practices
Technical Leadership
People Management