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

Apply Now

Senior Data Scientist - Drug Discovery - fully remote in UK

Hays
Manchester
3 weeks ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist - Financial Services - Outside IR35

Senior Data Scientists

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Your new company
You will be joining an expanding consultancy focused on supporting innovation in the pharmaceutical and biotech industry. Its specialist research division is dedicated to solving complex biological problems through advanced statistical modelling and ML/AI. They have an experienced team with a strong track record and are looking for an extra person to join them to work on statistical method development and application to real-world drug discovery & development problems.


Your new role
As a Senior Data Scientist, your work will centre on methodological innovation. You will:

  • Design and implement novel statistical approaches to interrogate large-scale genomic datasets
  • Develop new models to quantify genetic contributions to disease and complex traits
  • Evaluate and refine existing analytical frameworks to improve accuracy and interpretability
  • Ensure scientific rigour and reproducibility in all method development
  • Translate complex statistical outputs into meaningful insights for technical and non-technical audiences
  • Collaborate with engineering teams to embed new methods into scalable data pipelines
  • Contribute to peer-reviewed publications that showcase methodological advancements
  • Stay ahead of emerging techniques in statistical genetics and bioinformatics, integrating them into ongoing research


While pharma/biotech or consultancy industry experience is preferred, this role could also suit a recent PhD graduate or junior post-doc researcher with strong statistical method development.

The role can be fuly home based, or you can work from one of the company's offices across the UK.


What you'll need to succeed

  • PhD (or Master's with substantial experience) in statistics, maths, physics, data science, computing, statistical genetics or a related field with a strong methodological focus (or equivalent experience)
  • Demonstrated ability to create and validate new statistical / analytical models or workflows
  • Strong programming skills in R or Python, with experience in statistical libraries and bioinformatics tools
  • Familiarity with biobank-scale datasets and genomic databases
  • Experience with cloud platforms and scalable computing environments
  • A publication record that reflects methodological contributions to the field
  • Good communication skills, especially in explaining statistical concepts to diverse audiences



What you'll get in return
You'll be joining a highly experienced team doing cutting-edge work to support drug discovery & development efforts at a wide range of pharmaceutical and biotech companies. As well as lots of opportunities to develop your skills and career, this role offers a good package and the chance to make a significant impact.


What you need to do now
If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now.
If this job isn't quite right for you but you are looking for a new position, please contact us for a confidential discussion on your career.

Keywords: Statistical, Genetics, Bioinformatics, Genomics, Data, Scientist, Lead, Senior, GWAS, Polygenic, Risk, Score, Mendelian, Randomisation, Causal, Inference, Computational, Biology, Genetic, Epidemiology, Variant, Annotation, Pathway, Method, Enrichment, Protein, Interaction, Networks, Biobank, Research, Modelling, Development

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.

Careers

The Future of Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has become one of the most powerful forces reshaping the modern world. From voice assistants and recommendation engines to fraud detection and medical imaging, it underpins countless applications. ML is no longer confined to research labs—it powers business models, public services, and consumer technologies across the globe. In the UK, demand for machine learning professionals has risen dramatically. Organisations in finance, retail, healthcare, and defence are embedding ML into their operations. Start-ups in Cambridge, London, and Edinburgh are pioneering innovations, while government-backed initiatives aim to position the UK as a global AI leader. Salaries for ML engineers and researchers are among the highest in the tech sector. Yet despite its current importance, machine learning is only at the beginning of its journey. Advances in generative AI, quantum computing, robotics, and ethical governance will reshape the profession. Many of the most vital machine learning jobs of the next two decades don’t exist today. This article explores why new careers will emerge, the roles likely to appear, how today’s roles will evolve, why the UK is well positioned, and how professionals can prepare now.

Jobs

Seasonal Hiring Peaks for Machine Learning Jobs: The Best Months to Apply & Why

The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.

Jobs

Pre-Employment Checks for Machine Learning Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in machine learning reflects the discipline's unique position at the intersection of artificial intelligence research, algorithmic decision-making, and transformative business automation. Machine learning professionals often have privileged access to proprietary datasets, cutting-edge algorithms, and strategic AI systems that form the foundation of organizational competitive advantage and automated decision-making capabilities. The machine learning industry operates within complex regulatory frameworks spanning AI governance directives, algorithmic accountability requirements, and emerging ML ethics regulations. Machine learning specialists must demonstrate not only technical competence in model development and deployment but also deep understanding of algorithmic fairness, AI safety principles, and the societal implications of automated decision-making at scale. Modern machine learning roles frequently involve developing systems that impact hiring decisions, financial services, healthcare diagnostics, and autonomous operations across multiple regulatory jurisdictions and ethical frameworks simultaneously. The combination of algorithmic influence, predictive capabilities, and automated decision-making authority makes thorough candidate verification essential for maintaining compliance, fairness, and public trust in AI-powered systems.

🍪 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.