Risk Analytics Manager

Ouro is a global, vertically-integrated financial services and technology company dedicated to the delivery of innovative financial empowerment solutions to consumers worldwide. Ouro's financial products and services span prepaid, debit, cross-border payments, and loyalty solutions for consumers and enterprise partners. Since its founding in 1999 by industry pioneers, Ouro products have processed billions of dollars in transaction volume and served millions of customers worldwide. The company is headquartered in Austin, Texas with regional offices around the world. Location Austin, TX Employment Type Full time Department Payments & Risk About the Company Netspend provides prepaid and debit account solutions that connect customers with secure, convenient access to global payment networks so they can manage their money and make everyday purchases. With a nationwide U.S. retail network, customers can purchase and reload Netspend products at 130,000 reload points and over 100,000 distributing locations. Since our founding in 1999 by industry pioneers, Netspend products have processed billions of dollars in transaction volume and served millions of customers worldwide. The company is headquartered in Austin, Texas with employees worldwide. About the Role The Risk Data Analytics team is looking for a manager to help the team with building visualizations and monitoring, tracking KPI’s, working on data analysis to find opportunities to reduce losses and friction on our products, delivering more value to our customers by identifying risk strategy opportunities, writing documentation on data concepts, and automate internal processes within the risk and ops teams. This hands‑on role will report directly to the VP of Risk Data Science and Analytics. Responsibilities Lead, mentor, and manage a team of Risk Analysts, fostering a high-performance, collaborative, and innovative team culture. Dedicate approximately 20% of time to individual contributor (IC) work, actively contributing to core analytical projects and maintaining hands‑on technical proficiency. Define, prioritize, and oversee the Risk Analytics roadmap, ensuring alignment with overall Risk Department and company objectives. Set standards for terms, metrics, data visualization, reporting, and automation across the risk department, ensuring accuracy, consistency, and timely delivery. Conduct performance reviews, provide constructive feedback, and support the professional development of team members. Serve as the primary point of contact for stakeholders on Risk Analytics deliverables, translating complex analytical findings into clear, actionable business recommendations for executive leadership and cross‑functional teams. Drive the strategic analysis of transaction and customer data to proactively identify emerging fraud and credit risk trends and propose innovative control strategies. Collaborate closely with coworkers in the Risk Data Science, Risk, and Ops teams. Build and optimize queries, determine best sources and approach for data and insights. Assist in determining, scoping, and creating data products and data governance related to the Risk Data Science team. Engage on both strategic ad‑hoc requests and projects, conducting independent research to propose rules and strategies to help mitigate risks across all products. Proactively stay updated on industry trends, best practices, and regulatory requirements related to risk management and fraud prevention. Requirements Must have a high level of proficiency in using SQL for data analysis. Must have experience managing direct reports. Demonstrated ability to be a hands‑on leader, committed to coaching and developing junior analysts in SQL querying, rigorous data analysis techniques, effective presentation skills, and clear communication of complex findings. Experience with building data visualizations and dashboards (Qlik preferred, or Tableau, Looker, Power BI, etc.). Strong analytical skills with the ability to work with large datasets to identify patterns, trends, and anomalies in time series data is preferred. BS or advanced degree in STEM or related field is preferred. 5+ years’ experience in data analysis or related roles, preferably in the Fintech or Payments industry. Familiarity with card payments or banking/finance industry, including knowledge of transactional payment data analysis, experience with card association Risk and Dispute process/procedures is highly preferred but not mandatory for this role. Must be able to clearly communicate with technical and non‑technical audiences. Must be a team player and regularly collaborate with team members to enhance the culture of helpfulness and high impact. #J-18808-Ljbffr