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 models, feature infrastructure, graph intelligence, and MLOps capabilities across various payment and banking products. Your daily work involves partnering with Data Science, Engineering, Fraud Operations, and Model Risk Management to detect fraud rings and sophisticated schemes while maintaining a positive customer experience. You will oversee the productization of graph intelligence, including entity schema design and feature store architecture, while managing an experimentation roadmap for production capabilities. Required expertise includes Transformer-based ML systems, graph neural networks, sequence modeling, reinforcement learning, and MLOps practices. You must possess advanced knowledge of the product development life cycle, data analytics, and requirements definition to solve complex fraud challenges.
What does a Product Manager earn in New York?
Median $195400 from 109 postings across 30 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 delivery of capabilities.
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
Data Analytics
Product Development Life Cycle
Sequence Modeling
Reinforcement Learning
Adversarial ML
Graph Neural Networks
Streaming Features
Agentic AI
AI Inference
RAG
Speculative Decode
Vector Databases
Model Serving
CPU
Datacenter Platforms
Cloud Infrastructure
Benchmarking
Performance Optimization