Loss Prevention Program Lead

Job Description

Job Description

Job Title : Loss Prevention Program Lead

Company Overview :

Noetiq Edge is a strategic consulting firm based in Canada that provides expertise and insights to firms across multiple industries including Finance, Supply Chain, Retail, Healthcare, and High-tech.

We establish trusted partnerships with organizations to ensure they have the strategy, information, technology, and talent required to succeed in a dynamic world.

Job Description :

We are seeking a Loss Prevention Program Lead in Canada. This position is a permanent position, but also available as a contract-based position for the right candidate.

The LP Program Lead will help lead the design, modernization, and implementation of next-generation loss prevention (LP) solutions. This role is ideal for a strategic leader with deep expertise in risk, technology-driven loss prevention, and operational excellence. The successful candidate will help re-imagine loss prevention programs to deliver measurable results, leveraging analytics, automation, and best-in-class practices to reduce shrink, mitigate risk, and protect profitability.

Why this role is important :

Retail shrink, fraud, and compliance issues cost billions annually. This role is a critical part of transforming the business into a risk-aware, resilient, and customer-conscious operation, with loss prevention at the forefront of innovation

Key Responsibilities :

• Lead the transformation of legacy loss prevention strategies into a modern, technology-enabled solution suite.
• Develop frameworks that integrate data analytics, AI, automation, and IoT tools to predict, detect, and prevent losses across retail and supply chain operations.
• Partner with senior executives and clients to assess current LP programs, identify gaps, and build road maps for modernization
• Align loss prevention strategies with broader organizational goals such as customer experience, digital transformation, and operational efficiency.
• Evaluate and deploy emerging technologies (e.g., advanced video

analytics, RFID, predictive modelling, machine learning).

Required skills :

Nice-to-have skills :