Profit Protection Data and Analytics Manager

About the role

The Profit Protection Data & Analytics Manager leads the development and delivery of data-driven insight, intelligence and analytics that identify, predict, prevent and reduce losses across the organisation. The role turns data into actionable business intelligence for retail, ecommerce, supply chain, logistics, customer operations and security, working with Profit Protection, Security, Finance, Retail, Digital and Supply Chain stakeholders. It combines strategic leadership, technical expertise and commercial acumen.

Key responsibilities

• Data strategy and analytics leadership: build the analytics roadmap, reporting frameworks and KPIs to measure loss, fraud, shrinkage and operational risk.
• Commercial and loss intelligence: identify trends and threats in retail loss, ecommerce fraud, discount abuse, chargebacks, returns abuse, internal theft, supply chain losses and counterfeit activity.
• Predictive modelling: develop models for loss prediction and fraud detection using machine learning, statistics and automation, and lead scenario modelling and forecasting.
• Data governance: ensure data quality, integrity, standards and compliance with privacy and security requirements.
• Reporting and visualisation: maintain executive dashboards and present findings to senior leaders.
• Investigations support: provide data-backed insight for fraud, misconduct and loss investigations and partner with Security, Legal, Audit, Finance and HR.
• Stakeholder engagement: act as subject matter expert and champion a data-driven approach to risk reduction.
• Team leadership: lead, coach and develop analysts and allocate resources effectively.

Required profile

• Significant experience in data analytics, business intelligence, fraud analytics, risk analytics or profit protection.
• Experience managing analytical teams and delivering large-scale data initiatives.
• Strong commercial understanding of retail, ecommerce, logistics, security or supply chain.
• Proven ability to influence senior stakeholders and turn complex data into business recommendations.
• Desirable: retail, ecommerce, manufacturing or consumer goods experience, and knowledge of fraud prevention and investigations.

Required skills

• SQL and database querying
• Tableau, Power BI, Looker or equivalent visualisation tools
• Cloud platforms such as Google Cloud Platform, Azure or AWS
• Advanced Excel and data modelling
• Statistical analysis and predictive analytics
• Data governance and data quality management