Fraud Specialist/Analyst

Notes: • Looking for a consultant who has a strong background in fraud prevention or risk management • Would like someone to have experience in a SaaS or an e-commerce environment • Must be proficient in SQL - they need to have strong experience with Snowflake and Tableau • Must have excellent communication skills Key Responsibilities: • Monitor and analyze fraud KPIs. Define, track, and report on fraud metrics-including block vs. false positive rates, incoming fraud pressure, recall, fraud?to?sales ratio, and good user approval rate. Use these indicators to identify trends and gaps, fine?tune rules, and measure false/positive impacts. • Validate false positives. Perform manual reviews for flagged trials and purchases, verifying legitimate customers are not incorrectly declined. Work with internal stakeholders to reinstate valid users and gather feedback on user experience. • Design and refine controls. Test and adjust fraud detection rules, scoring models and machinellearning algorithms to mitigate risk without overblocking. Ensure models maintain high precision and recall while keeping false positives low. • Lead incident response. Coordinate investigations of fraud alerts and chargebacks, ensuring timely resolution and communication with affected stakeholders. Document root causes and adjust processes to prevent future incidents. • Cross functional collaboration. Partner closely with Product, Marketing, Engineering, Data Science, Legal, Finance and Customer Support teams to integrate fraud controls into product flows, billing systems and compliance processes. • Act as the primary point of contact and subject matter expert for all fraud-related matters within the organization. Basic Qualifications: • Bachelor's degree in Business, Economics, Data Science, or a related field • 5+ years of experience in fraud prevention, trust & safety, or risk management-ideally within a SaaS, ecommerce, or fintech environment. • Demonstrated ability to analyze large datasets, identify patterns, and drive data?driven decisions. • Proficiency in SQL and experience with data tools such as Snowflake and Tableau. • Deep understanding of fraud typologies (payment fraud, SaaS fraud, friendly fraud) and experience with fraud detection platforms, rule engines and case?management tools. • Excellent communication and interpersonal skills; comfortable collaborating with diverse teams and presenting insights to executives. Preferred Qualifications: • Familiarity with applying machine/learning models in fraud detection contexts. • Knowledge of payment processing ecosystems, card networks, and authentication methods. • Understanding of regulatory and compliance frameworks (e.g., Visa/MasterCard Risk monitoring programs, PCI?DSS). Apply tot his job