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 niall.wharton@Xcede.com (feel free to include a CV for review).