About the Opportunity Lead the full lifecycle of financial risk strategy development and implementation—from identifying opportunities to designing, testing, launching, and monitoring post-production performance. Detect, investigate, and track fraudulent or suspicious activities, including identifying and quantifying key trends impacting fraud and payment behaviors. Analyze both internal and external datasets to deliver detailed reports and root-cause analyses on fraud incidents and chargebacks. Collaborate closely with engineers and product managers to implement fraud prevention solutions that support business growth while maintaining strong risk controls. Serve as the primary point of contact with payment processors and vendors, leveraging strong communication skills to manage relationships, align on risk strategies, and navigate industry terminology. Experienced in handling transactions across multiple currencies, including USD, CAD, and others. About You The ideal candidate is a reliable and resilient team player who combines strong business judgment, technical expertise, and advanced analytical skills to support Snaplli’s rapid growth. Minimum of 5 years of professional experience, including at least 3 years in a fraud-related role and 1 year within the payments industry. Experience working with multiple payment methods in multi-currency environments, preferably in e-commerce or similar industries. Demonstrated ability to investigate and detect fraudulent activity, with hands‑on experience conducting transaction reviews and fraud case investigations. Strong background in data modeling (3+ years), including building fraud detection models, user behavior scoring systems, and transaction anomaly detection models. Experience with feature engineering, model training, evaluation, and deployment is required. Experience integrating models into risk systems to support automated, model-driven fraud prevention processes. Proficiency with machine learning frameworks (Python or R using tools such as Sklearn, XGBoost, or LightGBM) and experience deploying models in production environments. Strong SQL skills (required) with the ability to independently query and analyze large datasets; Python experience is a plus. Previous experience in roles such as Fraud Analyst, Risk Analyst, Operations Specialist, Data Scientist, or Product Manager. A bachelor’s degree in Engineering, Computer Science, Statistics, Finance, or a related analytical or technical discipline is preferred. Strong problem‑solving and analytical thinking abilities, including the capacity to think from a fraudster’s perspective to anticipate and mitigate risks. Mandarin Chinese proficiency is considered an asset but is not required. Pay Range $110,000 - $160,000 per year How to Apply Click the “Apply Now” button and follow the instructions to submit your resume. Please know that we only accept documents in MS Word or Rich Text formats. When referencing this job, quote # This position for employment is for a current vacancy withVaco/Highspring’sclient. You must currently reside within the Greater Toronto Area and be permitted to work in Canada to be considered for this opportunity. A recruiter will be in touch with you if your profile meets our client’s requirements for this role. #J-18808-Ljbffr