Core Cash Fraud Prevention Product Manager, Payments, Vice President

JPMorgan Chase

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Quick summary

Work type: On-site
Location: Chicago, ILTampa, FL
Employment: Full-time
Posted: 109 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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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 1226 open roles on FindRole.

Listed pay typically runs $156,750–$215,000 across 5 roles with salary data.

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At a glance

TL;DR · Core Cash Fraud Prevention Product Manager, Payments, Vice President

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JOB TITLE: Core Cash Fraud Prevention Product Manager - Payments - Vice President As a Vice President in the Core Cash Fraud Prevention team, you will lead the end-to-end product life cycle for innovative fraud prevention solutions. You will design, develop, and implement a new Global Fraud Consortium data platform and business rules to improve detection models for core cash payment channels including Wires, ACH, RTP, and emerging methods. Your daily work involves managing product backlogs using Agile methodologies, conducting market research on threat analysis, and collaborating with data science teams to deploy machine learning models. You must utilize SQL, JIRA, and Swagger for API design while ensuring compliance with regional regulations. You will solve complex problems regarding fraud patterns, attack vectors, and typologies to balance detection effectiveness with customer experience across US, EMEA, and APAC jurisdictions.

Skills

Agile JIRA SQL Machine Learning API Design Swagger ISO 20022 JSON XML SOAP Product Development Life Cycle Data Analytics Fraud Detection Systems Rule-based Engines INVEST Principles ACH RTP Wires

What you'll do

Lead the design, development, and implementation of a new Global Fraud Consortium data platform and business rules.
Develop a product strategy and vision aligned with business objectives and fraud prevention risk appetite.
Manage discovery efforts and market research to identify fraud patterns and integrate solutions into the product roadmap.
Own and maintain the product backlog using Agile methodologies to support the strategic roadmap.
Track key success metrics including cost, reliability, fraud detection effectiveness, and false positive rates.
Analyze fraud trends and attack vectors to enhance detection capabilities while balancing customer experience.
Collaborate with data science teams to develop and deploy machine learning models for the platform.
Design fraud detection mechanisms that comply with regional regulatory requirements and reporting obligations.

What we're looking for

Bachelor's or Master's degree in Engineering, Computer Science, Mathematics, or a related quantitative field.
5+ years of experience or equivalent expertise in product management or a relevant domain area.
Minimum 3 years of Financial Technology experience with deep understanding of Banking Payment Domain including Wires, ACH, RTP, and ISO 20022 standards.
Extensive experience with fraud detection systems, patterns, typologies, attack vectors, and fraud case management workflows.
Advanced knowledge of the product development life cycle, design, and data analytics.
Proven experience designing and implementing payment and fraud prevention solutions.
Strong proficiency in Agile development methodologies and tools like JIRA, including writing user stories following INVEST principles.
Experience with API design, contract definition (Swagger), and web service protocols (SOAP, XML, JSON).
SQL and database scripting capabilities to analyze large datasets.
Strong understanding of regional payment regulations and fraud prevention requirements across US, EMEA, and APAC jurisdictions.
6-12 years of experience in software development or technology companies (preferred).
Expertise in fraud detection methodologies, machine learning models, and rule-based engines (preferred).
Experience with fraud detection rule engines and scoring models (preferred).
Demonstrated prior experience working in a highly matrixed, complex organization (preferred).

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