Product Manager, Risk Products

Visa•Atlanta, GA

2d•Onsite

About The Position

Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters — to you, to your community, and to the world. Progress starts with you. We are looking for a strategic, commercially minded, client‑centric, and technically fluent Product Manager to drive the analytics, reporting, and insights capabilities of our Integrated Risk Platform—a core component of Visa’s mission to protect the global payments ecosystem through real‑time fraud detection, risk scoring, and intelligent decisioning. In this role, you will lead Analytics, Reporting, & Insights capabilities that serve as a core component of the Visa Integrated Risk Platform. In this role you will closely collaborate with Engineering, Data Science, and client-facing teams to deliver intelligent, scalable, and high-performance capabilities global in a SaaS delivery model. You will be responsible for translating complex stakeholder needs into platform solutions that reduce fraud, enhance trust, and drive measurable outcomes for our diverse client base - including Issuers, Acquirers, FinTech’s, Merchants, and Networks. What You’ll Build Fraud Analytics & Reporting You will define and deliver next‑generation analytics and reporting capabilities that serve as a core component of the Visa Risk Platform. Real-time KPI dashboards for fraud trends, case volumes, decision summaries, fraud prevented, etc. Analyst & Supervisor views with queue health, SLA tracking, and team performance metrics. Root-cause exploration tools for false positives, false negatives, and decision flows. Global risk visibility tools enabling partners to benchmark performance against peers. Performance Dashboards: Deliver real‑time dashboards that track fraud rule usage, fraud metrics, operational performance, decision quality, and fraud strategy health. AI-Powered Fraud Insights Partner with Visa’s AI/ML & research teams to integrate: GenAI summaries of fraud trends and anomalies. Agentic analytics to proactively investigate data shifts. Predictive insights for emerging fraud patterns. Anomaly detection for real-time behavioral spikes. Enterprise-Grade Reporting Engine Design a scalable reporting platform with: Configurable reports across tenants, geographies, and product lines. Scheduled delivery with precision filtering and compliance alignment. Export, APIs & data sharing for enterprise data teams. Strong governance around multi-tenant data access and role-based visibility.

Requirements

5 or more years of relevant work experience with a Bachelors Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD

Nice To Haves

6 or more years of work experience with a Bachelors Degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or up to 3 years of relevant experience with a PhD
5+ years of product management experience, with at least 2 years building consumer facing products
Proven track record of successfully launching and managing products
Experience in fraud, risk, payments, financial services, or other highly regulated domains , with an understanding of real‑time decisioning and data accuracy requirements.
Hands‑on experience delivering analytics dashboards, reporting tools, or insight platforms , including KPIs, operational metrics, and performance monitoring.
Familiarity with AI/ML‑enabled products , including GenAI, predictive analytics, anomaly detection, or decision‑support systems.
Experience applying responsible AI principles , including transparency, explainability, and fairness, in production systems.
Strong understanding of data models, pipelines, metrics definitions, and governance in enterprise environments.
Experience building self‑service, configurable reporting solutions with role‑based access and multi‑tenant data controls.
Ability to operate in a fast‑paced, global environment , balancing long‑term platform strategy with near‑term delivery.

Responsibilities

Product Strategy & Vision Define the long-term strategy for Visa’s fraud analytics & Reporting platform
Build a clear roadmap across dashboards, data models, AI insights, and reporting APIs
Align with cross-functional teams across Visa’s Integrated Risk Platform
Platform Product Leadership Lead an API-driven, multi-tenant analytics platform supporting multiple Visa products
Write clear, well‑structured Epics and Features that translate strategy into actionable engineering work.
Track the status of epics, features, and in-flight deliverables across engineering squads
Champion platform-first design, reusable components, and modular architecture
Ensure the analytics and reporting platform capability supports onboarding, automation, and self-service
Track key performance indicators around adoption, usage, latency, and platform health
Conduct continuous backlog grooming, roadmap updates, and release planning. Ensure the product backlog remains healthy, prioritized, and aligned to platform strategy.
AI & Data-Driven Product Management Integrate AI/ML capabilities to improve insights and user productivity
Use GenAI tools for prototyping, narrative generation, and user research
Apply AI-driven analytics to understand customer behavior and product performance
Ensure responsible AI practices (transparency, fairness, explainability)
Stay current on emerging AI technologies and assess where to apply them
Cross-Functional Collaboration Work closely with engineering, data science, design, risk experts, and customer-facing teams
Partner with PMs across Rules, Case Management, Identity, and other Foundational Services
Gather customer feedback and incorporate it into product improvements
Communicate roadmap and updates to leadership and stakeholders
Partner with data engineering to define models, pipelines, and metrics
Ensure data quality, accuracy, and consistency across all reporting products