Lead Data Scientist...

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).