Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Lead Genomics Data Scientist

London
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Genomic Data Scientist — Genome Annotation Pipelines

Senior Genomic Data Scientist (we have office locations in Cambridge, Leeds & London)

Senior Genomic Data Scientist (we have office locations in Cambridge, Leeds & London)

Senior Genomic Data Scientist (we have office locations in Cambridge, Leeds & London) London

Lead Data Scientist

Data Engineer

We are excited to announce that we are currently seeking a talented Lead Data Scientist. This is a unique opportunity to lead a range of cancer genome analysis and interpretation projects in collaboration with both external researchers and industrial partners.

As the Lead Data Scientist, you will play a crucial role in enhancing customised cancer genome analysis within our research environment. You will actively contribute to the development and implementation of best practices for genome analysis, spearhead end-to-end complex genomic analysis projects, and conduct benchmarking exercises for tools used in processing, analysis, and interpretation of whole genome data.

We are looking for someone who has in-depth expertise in cancer genomics, with a solid understanding of tumor drivers and interpreting genomic data through targeted pathways. You should be proficient in utilising Python for efficient data processing and analysis and hands-on experience in developing high-quality and reusable code, with a strong command of Git and CI/CD practices.

To excel in this role, you should have a PhD degree or equivalent practical experience in an industry setting and experience in leading a cross-functional analytical team in an academic or industry environment. You should also have a good understanding of biomedical challenges and a commitment to producing high-quality code.

The company is committed to ensuring the adherence to high standards of relevance, excellence, and clinical safety in genomic analysis, aligning with the business accreditation requirements. You will collaborate seamlessly with internal and external stakeholders to guarantee the successful delivery of projects and employ and critically evaluate statistical genetics analysis methods to derive insights from large-scale genomic data.

If you are looking for a technical and scientific leadership role in the realms of cancer genome analysis, then this is the ideal opportunity for you. Apply now and take charge of managing and leading an inclusive, high-performing team, ensuring the presence of the right skills to fulfil the company mission.

Carbon60, Lorien & SRG - The Impellam Group STEM Portfolio are acting as an Employment Business in relation to this vacancy

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Jobs

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Jobs

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.