Lead Data Scientist

JR United Kingdom; England; On-site; GBP 70,000 - 100,000; Full time

Job summary

A leading product-led business in the UK is seeking a Lead Data Scientist to guide a high-performing team. This role allows for significant autonomy in shaping the modelling roadmap, driving AI/ML initiatives, and ensuring the development of production-grade models in an innovative environment. Suitable candidates should possess substantial experience in applying data science solutions to create tangible business outcomes.

Qualifications

• 6+ years of hands-on experience applying data science techniques.
• Advanced academic background in a technical or quantitative field.
• Strong programming ability in Python and SQL.

Responsibilities

• Lead a team of data scientists to deliver impactful AI/ML initiatives.
• Design and implement predictive models and machine learning solutions.
• Collaborate with stakeholders to define modeling goals and demonstrate business value.

Skills

Leadership

Machine Learning

Statistical Techniques

Programming in Python

SQL

Data Handling

Experiment Design

Version Control

Data Processing

Geospatial Data

Education

MSc or PhD in Machine Learning, Computer Science, or Statistics

Tools

Databricks

Apache Spark

Git

Flask

Keras

Job description

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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 [emailprotected] (feel free to include a CV for review).