We are seeking a strategic and data-driven fraud and risk leader to join our Risk & Payments team. This role will shape and implement cutting‑edge risk strategies that drive sustainable growth, minimize losses, and enhance the customer experience. The ideal candidate has direct experience in payment fraud detection and prevention, with the ability to spot fraudulent transactions and translate fraud patterns into scalable, data‑driven solutions. This role requires a balance of hands‑on fraud investigation, SQL‑driven analytics, and collaboration with product and engineering teams to design and implement automated fraud controls. Location Toronto, Canada Key Responsibilities Lead the end‑to‑end development and execution of financial risk strategies—from opportunity identification to design, testing, launch, and post‑production performance monitoring. Identify, investigate and monitor fraudulent or anomalous activity, including isolating and quantifying specific trends driving changes to fraud and payment patterns. Analyze internal and external data and produce authoritative reports and root‑cause analysis on fraudulent activities and chargebacks. Experienced in collaborating with engineers and product managers to successfully deploy fraud prevention solutions that balance growth with risk control. Act as a liaison between the company and payment processors/vendors, with strong communication skills to speak the industry language, manage vendor relationships, and ensure effective alignment on fraud and risk management. Qualifications Experience working with various payment methods in multi‑currency environments, ideally within e‑commerce or related industries. Minimum 5 years of professional work experience; Minimum 3 years in a fraud‑related role; Minimum 1 year in the payments industry. Strong data modeling skills (3+ years) Proven ability to investigate and identify fraudulent activities, including hands‑on experience with transaction reviews and fraud case analysis. Ability to integrate models with risk systems to enable automated, model‑driven fraud prevention workflows. Proficiency with machine learning frameworks (Python or R with Sklearn, XGBoost, LightGBM, etc.) and prior experience deploying models into production environments. SQL proficiency (must‑have) — able to independently query and analyze large datasets. Python (good‑to‑have). Proficiency in Mandarin Chinese is an asset but not required. #J-18808-Ljbffr