This listing doesn't post a salary. Most similar roles pay
$177,050–$224,475.
Based on 240 similar postings.
Employer
About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1117 open roles
on FindRole.
Listed pay typically runs
$186,160–$215,000
across 7 roles with salary data.
As a Product Manager - Fraud AI/ML within the Fraud Strategy organization, you will define and drive the multi-year vision for advanced fraud prevention platforms. You will manage the roadmap for machine learning, graph intelligence, and MLOps capabilities across all payment and banking products to detect fraud rings and sophisticated schemes. Your daily work involves overseeing feature infrastructure, including streaming features, feature store architecture, and entity schema design while ensuring online and offline parity. You will partner with Data Science, Engineering, Fraud Operations, and Model Risk Management teams to convert proof-of-concepts into production capabilities. The role requires expertise in Transformer-based ML systems, graph neural networks, sequence modeling, reinforcement learning, and MLOps practices. You must possess strong skills in the product development life cycle, data analytics, and communicating complex technical concepts to executive leadership.
What does a Product Manager earn?
Median $204200 from 424 postings across 77 companies.
Define and communicate a multi-year roadmap for fraud models, feature infrastructure, graph intelligence, and MLOps capabilities.
Manage an experimentation roadmap to convert proven proof-of-concepts into production features that reduce fraud loss.
Design the dynamic feature ecosystem including streaming features, discovery processes, and feature store architecture.
Oversee the productization of graph intelligence for entity schema design, embedding strategy, and fraud ring detection.
Partner with cross-functional teams to address emerging fraud threats and ensure timely capability delivery.
Monitor industry trends in adversarial ML, graph neural networks, sequence modeling, and reinforcement learning.
Communicate complex technical concepts and platform capabilities clearly to executive leadership and stakeholders.
What we're looking for
Bachelor's degree required.
Authorization to work for any employer in the US.
5 years of experience in product management or a relevant domain area.
Advanced knowledge of the product development life cycle, design, and data analytics.
Proven ability to lead product life cycle activities including discovery, ideation, strategic development, requirements definition, and value management.
Experience with Transformer-based ML systems, graph intelligence, continuous learning platforms, or MLOps.
Machine Learning
MLOps
Graph Intelligence
Feature Store
Graph Neural Networks
Sequence Modeling
Reinforcement Learning
Adversarial ML
Data Analytics
Product Development Life Cycle
Streaming Features
Agentic AI
AI Inference
RAG
Speculative Decode
Vector Databases
Model Serving
CPU
Datacenter Platforms
Cloud Infrastructure
Benchmarking
Performance Optimization