Lead Data Scientist

We are recruiting for two experienced Lead Data Scientists to join a major enterprise data and analytics programme focused on transforming customer engagement, commercial performance and decision-making. These positions offer the opportunity to work on large-scale customer datasets, advanced machine learning solutions and business-critical analytical products that directly influence strategic decisions.

• Shape customer decisioning and analytics at enterprise scale.
• Deliver data science that drives measurable business value.

We are hiring for two specialist Lead Data Scientist positions.

Position 1: Decision Science, Optimisation & Production MLYou will lead the development and operationalisation of advanced decision-science capabilities, helping the business optimise customer engagement, campaign performance and commercial outcomes.

Key responsibilities include:

• Designing and deploying causal and uplift models to improve customer targeting and decisioning.
• Developing recommendation and optimisation models that balance customer outcomes with budget constraints.
• Building and maintaining production-grade machine learning solutions.
• Driving experimentation frameworks and performance measurement methodologies.
• Collaborating with engineering and business teams to ensure scalable model deployment and ongoing monitoring.
• Establishing best practices around model governance, version control and production support.

Position 2: Customer Intelligence, Incrementality & Value MeasurementYou will own the analytical frameworks used to measure customer value, campaign effectiveness and commercial impact across multiple markets.

Key responsibilities include:

• Leading customer analytics and incrementality measurement initiatives.
• Developing CLV, RFM and customer segmentation methodologies.
• Reconciling customer, transaction and financial datasets to establish trusted performance metrics.
• Building scalable analytical pipelines and reproducible value measurement frameworks.
• Creating robust scenario planning models and leadership reporting.
• Investigating and explaining differences between data sources, methodologies and reported outcomes.

Position 1: Decision Science, Optimisation & Production MLYou will possess:

• Advanced Python skills for machine learning, statistical analysis and production data science.
• Strong SQL capability across complex customer, campaign and transaction datasets.
• Extensive Databricks experience including workflows, Delta tables, model registries and production scoring.
• Experience with causal inference, uplift modelling, recommender systems or optimisation modelling.
• Strong understanding of MLOps, model monitoring and production deployment best practices.
• Experience using G it and Azure DevOps within controlled development environments.

Desirable:

• Databricks Apps, MLflow or Databricks Asset Bundles.
• Streamlit, Dash or React experience.
• CRM and customer activation platform exposure.
• Marketing science, optimisation or operations research experience.

Position 2: Customer Intelligence, Incrementality & Value MeasurementYou will possess:

• Advanced SQL skills for large-scale customer and transaction analysis.
• Strong Python expertise covering statistical modelling, matching methodologies and analytical product development.
• Hands-on Databricks, Spark or PySpark experience.
• Experience developing robust reconciliation, audit-trail and validation frameworks.
• Strong stakeholder management skills with the ability to explain complex analytical outcomes to senior audiences.
• Experience working with source-to-report analytical processes and enterprise-scale customer data.

Desirable:

• Loyalty, CRM or retail analytics experience.
• Power BI reporting expertise.
• Incremental processing and production data pipeline design.
• Experimentation, uplift validation or customer decisioning experience.