JD - The Fraud Strategy position leads the development of divisional fraud strategies to enhance business outcomes and minimize risks related to fraud. The role oversees fraud strategies for specific segments and involves utilizing statistical and predictive analytics, machine learning, and data visualization to design prevention strategies, provide actionable insights and consult with business leaders on leveraging these insights for strategic decision-making. This position will serve as a subject matter expert in the recommendation, development, implementation and monitoring of risk prevention and data programs. Core Responsibilities 1. Lead development of fraud strategies in fraud prevention systems. Independently perform sophisticated data analytics using structured and unstructured data. 1. Oversees and leads the divisional strategy for fraud strategy, including governance frameworks, data structures, and deliverables. Leverages deep analytics and statistics knowledge to determine risk, and develop plans for success. 1. Collects, analyzes, and communicates statistics related to daily fraud mitigation operations to stakeholders. 1. Leads and analyzes processes, products and reviews the validation of scalable analyses. Ensures products meet stakeholders' needs for information and insights. Develops a technology strategy and manages vendor relationships supporting the delivery of analytical capabilities. 1. Ensures alignment between department or team deliverables and enterprise goals and strategies. 1. Engages with strategic business and stakeholder relationships to understand and probe business processes in order to develop risk mitigation processes. Brings structure to requests and translates requirements into an analytic approach. Makes recommendations to key business partners or senior management as needed. 1. Continually develops understanding of industry trends and provides updates to the team to build business acumen. Champions change management efforts and advocates to ensure implementation of governance practices. 1. Participates in special projects and performs other duties as assigned. Qualifications • Minimum of eight years related work experience in fraud strategy or fraud data science field. • Hands-on experience in directly building fraud strategies or models in financial industry and cash products (New Account, ATO, money movement in Retail or Card products) • Strong familiarity with data extraction in environments like SQL. High proficiency in SQL and Python. Working knowledge of Python, Hive, Spark, AWS Sagemaker. • Experiences with Lexis fraud products, especially coding rules in TMX platform is huge plus • Experiences with machine learning is a plus. Understanding of statistical methods, including classical statistics, probability theory, econometrics, and time-series analysis. • Undergraduate degree or equivalent combination of training and experience. Graduate degree preferred.