Senior AI Product Manager - Risk Platform

Visa•Atlanta, GA

2d•Hybrid

About The Position

We are looking for a strategic, commercially minded, client‑centric, and technically fluent Senior 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

8 or more years of relevant work experience with a bachelor's degree or at least 5 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD)
Able to break down complex technical ideas into clear user value
Strong communicator who writes clearly, listens actively, and works well across teams
Uses data to make decisions and is comfortable with experimentation and A/B testing
Understands customer needs and applies design thinking to shape solutions
Balances innovation with practical delivery needs and business priorities
Comfortable operating in fast‑moving, ambiguous environments
Knowledge of global markets, competitive landscape and related dynamic
Uses strong customer empathy to identify real problems and partner with UX & other stakeholders to design meaningful, intuitive experiences.
Keeps the team aligned on the outcomes that matter most
Comfortable working with modern architectures like event‑driven systems, streaming data, and real‑time platforms
Good understanding of APIs, integrations, and how systems communicate
Familiar with AI/ML concepts and tools, including LLMs, embeddings, vector stores, or RAG
Awareness of UI/UX practices and ability to use quick prototyping tools when needed
Knowledge of cloud technologies (AWS preferred), data pipelines, and analytics tooling

Nice To Haves

10 or more years of relevant work experience with a bachelor's degree or at least 7 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD)
Technical background in Computer Science or Engineering
Experience with AI/ML products, Dashboard, and reporting particularly in production environments
Background in fintech, risk management, or financial services preferred
Demonstrated success launching technical products for non-technical users
Experience in building large scale, real-time mission critical platforms, experience in building Risk Platform is a plus

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