Profit Protection Data and Analytics Manager

The Profit Protection Data & Analytics Manager is responsible for leading the development and delivery of data-driven insight, intelligence, and analytics capabilities that identify, predict, prevent, and reduce losses across the organisation.

The role will transform data into actionable business intelligence, enabling informed decision-making across retail, ecommerce, supply chain, logistics, customer operations, and security functions. Working closely with Profit Protection, Security, Finance, Retail, Digital, and Supply Chain stakeholders, the manager will establish analytics frameworks that support fraud prevention, shrink reduction, risk identification, investigations, and operational performance improvement.

This role combines strategic leadership, technical expertise, and commercial acumen to create a proactive, insight-led Profit Protection capability that safeguards revenue, assets, products, and brand reputation. The function supports the wider objective of leveraging data to drive business insights that protect value and enable sustainable growth.

Key Responsibilities
Data Strategy & Analytics Leadership
• Develop and execute the Profit Protection data and analytics strategy aligned to business and security objectives.
• Create a roadmap for analytics maturity, predictive modelling, automation, and intelligence-led risk management.
• Lead the design and implementation of reporting frameworks that measure loss, fraud, shrinkage, and operational risk.
• Establish key performance indicators and success measures to monitor Profit Protection effectiveness.

Commercial & Loss Intelligence
• Identify trends, anomalies, and emerging threats using data from multiple sources across the business.
• Provide actionable intelligence relating to:
o Retail loss and shrinkage
o Ecommerce fraud
o Discount and promotion abuse
o Chargebacks and payment fraud
o Returns abuse
o Internal theft
o Supply chain and logistics losses
o Counterfeit activity
• Deliver strategic insight that improves profitability and reduces preventable losses.

Advanced Analytics & Predictive Modelling
• Develop analytical models that predict loss events, fraud patterns, and operational vulnerabilities.
• Apply machine learning, statistical analysis, and automation techniques to improve detection capability.
• Drive the adoption of AI-enabled analytics solutions where appropriate.
• Lead scenario modelling and forecasting activities to support strategic decision-making.

Data Management & Governance
• Ensure data quality, integrity, governance, and appropriate controls across all Profit Protection datasets.
• Define standards for data collection, reporting, and information management.
• Work with technology and data teams to improve accessibility and usability of data assets.
• Ensure compliance with privacy, data protection, and information security requirements.

Reporting & Visualisation
• Develop and maintain executive dashboards and management reporting suites.
• Ensure key stakeholders have access to timely, accurate, and meaningful insights.
• Present findings and recommendations to senior leaders in a clear and compelling manner.
• Translate complex technical analysis into practical business actions.

Investigations & Risk Support
• Support investigations through advanced data analysis and intelligence development.
• Provide evidence-based insight to assist fraud, misconduct, and loss investigations.
• Partner with Security, Legal, Audit, Finance, and HR teams where required.
• Identify root causes and recommend sustainable remediation actions.

Stakeholder Engagement
• Build strong relationships across Security, Finance, Retail, Ecommerce, Supply Chain, Digital, Data, and Technology teams.
• Act as the subject matter expert for Profit Protection analytics and intelligence.
• Influence senior stakeholders to adopt data-driven approaches to risk reduction and decision-making.
• Champion a culture of insight-led performance and continuous improvement.

Team Leadership
• Lead, coach, and develop analysts within the Data & Analytics function.
• Foster a culture of curiosity, innovation, accountability, and technical excellence.
• Ensure effective allocation of resources and prioritisation of analytical activities.
• Promote knowledge sharing and capability development across the wider organisation.

Experience & Qualifications
Essential
• 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 environments.
• Advanced experience using analytics platforms and visualisation tools.
• Proven ability to influence senior business stakeholders through data-driven insight.
• Experience translating complex datasets into actionable business recommendations.

Technical Skills
• SQL and database querying.
• Tableau, Power BI, Looker, or equivalent visualisation tools.
• Cloud-based data platforms (e.g., Google Cloud Platform, Azure, AWS).
• Advanced Excel and data modelling capabilities.
• Statistical analysis and predictive analytics.
• Data governance and data quality management.

Desirable
• Experience within retail, ecommerce, manufacturing, or consumer goods sectors.
• Knowledge of fraud prevention, investigations, loss prevention, or security intelligence.
• Experience applying machine learning and AI solutions to commercial challenges.
• Relevant qualifications in Data Analytics, Computer Science, Mathematics, Statistics, Risk Management, Security, or a related discipline.

Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity.