Data Scientist

Overview

In this role you will lead customer analytics and value measurement across markets, building robust CLV and segmentation models. You will partner with Finance and stakeholders to ensure reproducible value estimates, while developing scalable data pipelines and frameworks. Your work will shapes how we understand customer behavior and commercial performance, driving data-driven decisions in a complex, cross-market environment. This is a hands-on, impact-focused role rooted in advanced analytics and data integrity.

Responsibilities

• Lead customer analytics initiatives (CLV, RFM segmentation, incrementality, scenario planning)
• Reconcile customer, transaction, and margin data to produce trusted value estimates
• Develop and maintain analytical frameworks explaining performance drivers and data discrepancies
• Partner with Finance and business stakeholders to validate methodologies and operationalise value estimates
• Build scalable analytical solutions and pipelines using Databricks, Spark, and Python
• Establish data validation, audit, and reconciliation practices to support decision-making

Key requirements

• Advanced SQL for large-scale analysis
• Strong Python skills for statistical modelling and reproducible analytics
• Hands-on experience with Databricks, Spark/PySpark, Delta tables, and automated data workflows
• Proficiency with Git, Azure DevOps, and controlled production release processes
• Strong data quality, reconciliation, and audit-trail practices

• stakeholder collaboration
• attention to data quality
• problem solving and communication
• SQL
• Python
• Databricks

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