Associate Product Manager

Ria Money Transfer, a business segment of Euronet Worldwide, Inc. (NASDAQ: EEFT), delivers innovative financial services including fast, secure, and affordable global money transfers to millions of customers along with currency exchange, mobile top-up, bill payment and check cashing services, offering a reliable omnichannel experience. With over 600,000 locations in nearly 200 countries and territories, our purpose remains to open ways for a better everyday life.

We believe we can create a world in which people are empowered to build the life they dream of, no matter who they are or where they are. One customer, one family, one community at a time.

We are currently looking for a Full Time Associate Product Manager
- Checkout to join our growing team who will be responsible for supporting the Fraud and Payments squads within the Checkout domain. Working as a flexible resource across both teams, this role partners with the Product Managers to drive critical projects forward and keep the day-to-day operation running - from analyzing transaction and loss data and monitoring product KPIs, to writing requirements, coordinating with engineering and vendors, and closing the loop on operational escalations.

This is an ideal role for an analytically minded early-career product professional who wants deep exposure to payments, fraud prevention, and risk decisioning at global scale.

• Support the Fraud and Payments Product Managers in the day-to-day operation of the Checkout domain: triaging incoming issues and escalations, monitoring product dashboards and alerts, tracking vendor performance, and following up on open action items across both squads.
• Perform data analysis to support product decisions: write and run SQL queries against the data warehouse, build and maintain reports and dashboards (Excel, Amplitude, or similar analytics tools), and translate findings on approval rates, fraud losses, chargebacks, and payment performance into clear recommendations.
• Assist in the execution of critical projects across both squads: drafting product requirements and user stories, maintaining the backlog in Jira, coordinating with engineering, design, data, and external vendors, and tracking delivery milestones and launch readiness.
• Prepare recurring product reporting and business reviews: consolidate KPIs from both squads into weekly and monthly updates, document experiment results, and prepare materials for leadership and stakeholder presentations.
• Conduct discovery and research: analyze user behavior and funnel data, benchmark competitor and industry practices in payments and fraud prevention, and document findings to inform the product roadmap.
• Support vendor and partner management activities: help monitor SLAs and performance of fraud and payment providers, assist with data pulls for vendor evaluations, and document integration and process logic.
• Contribute to the continuous improvement of team processes: keep product documentation current, improve operational runbooks, and identify opportunities to automate recurring analyses and reports.

• Minimum of one (1) to three (3) years of experience in product management, product analytics, data analysis, or a related role - ideally in payments, fintech, fraud/risk, e-commerce, or another data-intensive digital product environment.
• Proven experience in data analysis and/or data science: proficiency in SQL is required; experience with Python or R, statistical analysis, or building dashboards in tools such as Amplitude, Tableau, or Power BI is strongly preferred.
• Demonstrated understanding of product management fundamentals: writing requirements and user stories, backlog management, agile ways of working, and working directly with engineering teams.
• Advanced Excel skills and comfort working with large datasets to produce accurate, decision-ready analysis.
• Experience with product and collaboration tools such as Jira, Confluence, and analytics platforms; familiarity with payment processing, fraud prevention, or risk decisioning systems is a plus.
• Strong analytical and problem-solving skills, with the rigor to validate data before drawing conclusions and the judgment to distinguish signal from noise.
• Excellent written and verbal communication skills, with the ability to synthesize complex technical and data topics for both technical and non-technical audiences.
• Highly organized and…