\r\n\r\nJob ID: R2000596641 \r\n \r\n\r\nJob Description:\r\n\r\n \r\n\r\nIn this key role, you will join a dynamic team dedicated to safeguarding our loyalty programs and retail operations from evolving fraud threats. You'll leverage your strong analytical skills to build scalable detection solutions, automate complex insights, and proactively identify new patterns, directly contributing to the financial integrity and customer trust of Loblaw Companies Limited.\r\n\r\n \r\n\r\nWhat You’ll Do:\r\n\r\n\r\n\tLead the development and implementation of scalable fraud detection strategies across Loyalty, Internal Retail, and other enterprise-wide fraud domains, translating granular patterns into broad-spectrum analytical solutions.\r\n\tDesign, build, and maintain advanced fraud analytics tools and automated queries to enhance the efficiency of fraud operations, maximizing detection while minimizing legitimate customer impact.\r\n\tCreate and manage comprehensive dashboards and reports that provide critical insights into evolving fraud trends and key performance indicators for various stakeholders.\r\n\tProactively identify emerging fraud vulnerabilities and collaborate extensively with cross-functional teams including Data Engineering, Cyber Security, Operations, and Asset Protection to implement robust preventative measures.\r\n\tAct as a self-starting leader and subject matter expert within the Fraud Analytics team, driving best practices and continuous improvement in our fraud detection capabilities.\r\n\r\n\r\n \r\n\r\nWhat you Bring:\r\n\r\n\r\n\tProven hands-on advanced proficiency in SQL and Python for complex data analysis, automation, and building analytical tools.\r\n\tHands-on experience with leading Business Intelligence (BI) tools, specifically Power BI and Looker, for creating impactful dashboards and reports.\r\n\t2+ years of experience in data analytics, with a preference for experience in fraud, risk, or a related domain.\r\n\tExceptional problem-solving and critical thinking skills, with a proven ability to translate complex data insights into clear, actionable recommendations.\r\n\tBachelor's degree in a quantitative field such as Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, or a related discipline.\r\n\r\n\r\n \r\n\r\nOur commitment to Sustainability and Social Impact is an essential part of the way we do business, and we focus our attention on areas where we can have the greatest impact. Our approach to sustainability and social impact is based on three pillars – Environment, Sourcing and Community – and we are constantly looking for ways to demonstrate leadership in these important areas. Our CORE Values – Care, Ownership, Respect and Excellence – guide all our decision-making and come to life through our Blue Culture. We offer our colleagues progressive careers, comprehensive training, flexibility, and other competitive benefits – these are some of the many reasons why we are one of Canada’s Top Employers, Canada’s Best Diversity Employers, Canada’s Greenest Employers & Canada’s Top Employers for Young People.\r\n\r\n \r\n\r\nIf you are unsure whether your experience matches every requirement above, we encourage you to apply anyway. We are looking for varied perspectives which include diverse experiences that we can add to our team.\r\n \r\n\r\nWe have a long-standing focus on diversity, equity and inclusion because we know it will make our company a better place to work and shop. We are committed to creating accessible environments for our colleagues, candidates and customers. Requests for accommodation due to a disability (which may be visible or invisible, temporary or permanent) can be made at any stage of application and employment. We encourage candidates to make their accommodation needs known so that we can provide equitable opportunities. \r\n \r\n \r\n\r\nPlease Note:\r\nCandidates who are 18 years or older are required to complete a criminal background check. Details will be provided through the application process.\r\n
