Lead Data Scientist
Surrey office, x1 day every two weeks.
A well-established, product-led business is looking for a Lead Data Scientist to spearhead innovation and drive measurable value through advanced machine learning, experimentation, and the development of production-grade models.
Sitting within a cross-functional data team, this is a hands-on leadership role with the autonomy to shape the modelling roadmap, contribute to R&D strategy, and influence pricing and risk decisions across multiple business lines. You’ll manage a small team of data scientists, guiding them through delivery while remaining actively involved in technical implementation and experimentation.
This is a unique opportunity for someone passionate about building machine learning systems that go beyond prototypes — models that deliver real-world commercial outcomes in a data-rich, regulated environment.
Key Responsibilities
Lead a high-performing team of data scientists to deliver cross-functional, impactful AI/ML initiatives
Design and implement predictive models and machine learning solutions for core business areas
Build and productionise models in collaboration with data engineers and platform teams
Apply advanced statistical techniques to extract insights and guide product and pricing strategies
Work closely with stakeholders to understand requirements, define modelling goals, and demonstrate business value
Evaluate vendor data sources, assess economic and technical feasibility, and lead test-and-learn initiatives
Contribute to the modelling roadmap, experimentation frameworks, and internal data science tooling
Produce clean, maintainable, version-controlled code and refactor solutions into reusable libraries and APIs
Coach junior team members and promote best practices across the wider data and analytics community
Requirements
Ideally, 6+ years of hands-on experience applying data science techniques in commercial or research-led environments, delivering clear business outcomes
Advanced academic background (MSc or PhD) in a technical or quantitative field such as Machine Learning, Computer Science, or Statistics
Strong programming ability in Python (data science ecosystem) and SQL, with proven experience handling large, complex datasets
Solid track record of building, validating, and deploying machine learning models into real-world systems
Practical experience designing experiments, selecting evaluation metrics, and applying multivariate testing frameworks
Leadership mindset — you’ve mentored or managed data science colleagues or helped steer technical decisions in a collaborative team
Comfortable with version control (Git) and familiar with engineering workflows like CI/CD and containerised environments
Skilled at working with both structured and unstructured data to unlock insights and power models
Hands-on experience with Databricks, Apache Spark, or similar tools used in large-scale data processing
Exposure to machine learning model deployment using APIs or lightweight serving frameworks like Flask or Keras
Familiarity with geospatial data would be a great bonus!
If this role interests you and you would like to learn more, please apply here or contact us via (feel free to include a CV for review).
