Head of Data Science in London

Qureight’s mission is to accelerate clinical trials and ensure breakthroughs in lung and heart disease reach patients without delay. Our AI-powered data and imaging curation platform enables the analysis of clinical imaging and other healthcare data, helping our customers bring treatments to market, faster. We’re looking for talented people who want their work to matter. With offices in Cambridge and London, you’ll join our multidisciplinary team of clinicians, scientists, and engineers. What unites us is our open culture, continuous learning mindset, and a shared mission to help biopharma run faster, smarter trials.

About the role: As Qureight scales its AI-driven imaging platform, we are building the data science capability required to translate machine learning outputs into clinically meaningful, trial-ready, and commercially valuable insights. We are looking for an exceptional Head of Data Science to lead this function. This role sits at the intersection of machine learning, clinical research, and product delivery, ensuring that our models generate outputs that are scientifically robust, clinically interpretable, and deployable in clinical trials and drug development. Reporting to the Chief Scientific Officer, this is a high-impact leadership role responsible for defining how data science supports the full pipeline from model development through to clinical and commercial use.

You will be responsible for:

• Defining the long-term data science strategy aligned with company objectives.
• Leading and scaling the data science function:
• Building and leading a high-performing data science team across model analysis, client analysis, and advanced methodologies.
• Defining and embedding best practices for reproducible, modular, and scalable data science pipelines.
• Setting standards for statistical validity, analytical rigor, and reproducibility of outputs across the organisation.
• Ensuring strong alignment with machine learning, data engineering, and clinical teams.
• Translating ML outputs into trial-ready products:
• Driving development of data science outputs that support commercial offerings and client value propositions.
• Owning the transformation of machine learning outputs into clinical trial endpoints, biomarker definitions, and statistical outputs used by sponsors.
• Ensuring outputs are scientifically valid, clinically interpretable, and suitable for regulatory use and use by sponsors.
• Developing advanced analytical methodologies:
• Leading development of methodologies including synthetic control arms, longitudinal modelling, and patient-level outcome modelling.
• Ensuring methods are robust, reproducible, and defensible in external settings.
• Driving scientific outputs and validation:
• Overseeing delivery of validation reports, abstracts and publications, and sponsor-facing analyses.
• Ensuring data science outputs reinforce Qureight’s scientific credibility.
• Representing the data science function in external scientific and commercial engagement.
• Partnering across the organisation:
• Working closely with ML, data engineering, clinical/translational, product, and commercial teams.
• Aligning data science outputs with productization and customer needs.
• Acting as a key bridge between technical teams and external stakeholders.
• Supporting trial delivery and sponsor engagement:
• Contributing to trial design and endpoint strategy.
• Translating complex outputs into clear, actionable insights.

What we need:

• Must have proven experience leading data science teams in complex, data-driven environments within healthcare, biotech, medtech, or clinical trial datasets.
• Strong background in statistical modelling, machine learning applications, and longitudinal data analysis.
• Track record of delivering high-quality scientific outputs (publications, validation studies, sponsor deliverables).
• Experience working cross-functionally with ML, engineering, and clinical teams.
• Strong communication skills, with the ability to translate technical outputs into clinical and commercial impact.
• Experience defining and executing data science strategy at team or organisational level.
• Experience delivering outputs in regulated or client-facing environments.

Even better if you have experience of:

• Synthetic control arms in clinical trials and/or causal inference.
• Quantitative imaging or imaging biomarkers.
• Regulatory or GxP environments.
• Pharma partnerships or clinical trial delivery.

What can you expect from us: A comprehensive benefits package that includes an annual bonus plan, private medical insurance, life insurance, and a contributory pension scheme. 25 days annual leave, plus.