As a Product Manager in the C360 team, you are an integral part of the organization that delivers core data products used every day across the firm. You will own the end-to-end product life cycle for resolving millions of organizational records from internal systems and third-party providers into a single, trusted global universe of entities, and producing an arbitrated “golden profile” that downstream platforms rely on. This is a product ownership role focused on shipping capabilities into production at scale, not an advisory or analytics-only role and requires strong operating discipline, technical fluency, and cross-functional leadership.
- Develops a product strategy and product vision that delivers customer value by establishing a single, trusted, global universe of organizations and an arbitrated “golden profile” that downstream teams and platforms can rely on in production.
- Manages discovery efforts and market research to uncover customer solutions and integrate them into the product roadmap, including partnering with front-office, operations, and control stakeholders to define measurable outcomes for match quality, duplicate reduction, profile completeness, and adoption.
- Owns, maintains, and develops a product backlog that enables development to support the overall strategic roadmap and value proposition, translating business needs into clear, testable requirements for entity resolution, attribute arbitration, challenge-and-override workflows, and data onboarding patterns.
- Builds the framework and tracks the product’s key success metrics such as cost, feature and functionality, risk posture, and reliability, including precision/recall and false positive/negative rates, resolution throughput and cycle time, duplicate creation rates, golden profile correctness and completeness, and service-level targets for adjudication workflows.
- Leads delivery of entity resolution at scale across internal systems and third-party sources by balancing deterministic rules with machine learning-assisted matching, ensuring resolution decisions are explainable, traceable, and auditable for downstream reliance.
- Owns the arbitration and “golden record” capabilities that select best attribute values using configurable logic (for example, consensus and recency), including workflows that allow expert challenge, override, and safe propagation of corrections with full provenance.
- Defines a third-party data onboarding strategy and operating model, prioritizing integrations based on business value and readiness, setting quality and documentation standards, and establishing scalable onboarding patterns that prevent uncontrolled schema sprawl.
- Delivers diagnostic and operational tooling that enables users and operators to understand why entities matched or did not match, how attribute selections were made, and where data quality issues are creating adverse outcomes.
- Introduces AI- and agent-assisted processing patterns to improve throughput and reduce manual intervention, while maintaining appropriate governance, human-in-the-loop controls, and objective evaluation of model performance over time.
- Partners closely with engineering, applied machine learning, architecture, data governance, and business stakeholders to manage dependencies, ensure resiliency and stability, and drive executive-ready communication on progress, risks, and trade-offs.
- 5+ years of experience or equivalent expertise in product management or a relevant domain area
- 3+ years of owning complex data products or platforms where correctness, scale, and adoption are equally critical.
- Demonstrated track record of shipping production products end-to-end, including roadmap ownership, backlog management, and measurable outcomes; experience delivering operationally supported platforms, not presentations.
- Strong technical fluency across data platform fundamentals, including entity modeling, mastering and arbitration patterns, metadata and lineage, provenance, and data quality dimensions.
- Ability to reason about algorithmic and operational trade-offs, including precision/recall, false positives/negatives, latency/throughput, and explainability versus automation, and to translate these into product decisions and success metrics.
- Experience working with cross-functional teams across engineering, data engineering, applied machine learning, operations, and governance, with proven ability to influence in a matrixed environment.
- Strong product operating discipline, including dependency management, release planning, clear requirements definition, and executive-level communication.
- Demonstrated prior experience working in a highly matrixed, complex organization
- Experience in financial services, particularly Corporate & Investment Banking, including exposure to enterprise data controls and audit expectations.
- Prior experience with entity resolution or identity matching, deterministic rules frameworks, and machine learning-assisted matching or classification in high-volume environments.
- Experience designing explainability, auditability, and human-in-the-loop governance patterns for AI-enabled production workflows.
- Experience sourcing, normalizing, and integrating third-party data, including establishing scalable onboarding patterns and quality standards.
- Familiarity with knowledge representation approaches such as knowledge graphs or ontology-driven modeling, particularly where downstream consumers require traceability and consistent semantics.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
Skills Required
- 5+ years of experience in product management or equivalent expertise
- 3+ years owning complex data products or platforms focused on correctness, scale, and adoption
- Demonstrated track record of shipping production products end-to-end with roadmap ownership and measurable outcomes
- Technical fluency in data platform fundamentals including entity modeling, mastering/arbitration patterns, metadata, lineage, provenance, and data quality
- Ability to reason about algorithmic and operational trade-offs (precision/recall, false positives/negatives, latency/throughput, explainability)
- Experience working with cross-functional teams (engineering, data engineering, applied ML, operations, governance) in a matrixed environment
- Strong product operating discipline including dependency management, release planning, clear requirements definition, and executive communication
- Prior experience working in a highly matrixed, complex organization
- Experience in financial services, particularly Corporate & Investment Banking, with exposure to enterprise data controls and audit expectations
- Prior experience with entity resolution or identity matching, deterministic rules frameworks, and ML-assisted matching in high-volume environments
- Experience designing explainability, auditability, and human-in-the-loop governance for AI-enabled production workflows
- Experience sourcing, normalizing, and integrating third-party data and establishing scalable onboarding patterns and quality standards
- Familiarity with knowledge representation approaches such as knowledge graphs or ontology-driven modeling
JPMorganChase Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.
-
Healthcare Strength — Medical, dental, vision, and mental health coverage are comprehensive, with on-site clinics, preventive care, and specialized supports such as maternity nurse guidance and fertility treatments. Wellness activities can help offset copays and out-of-pocket costs, reinforcing the perceived strength of health benefits.
-
Retirement Support — A 401(k) with dollar-for-dollar matching and additional automatic pay credits reflect strong employer-backed retirement savings. An employee stock purchase plan and related financial programs further bolster long-term financial support.
-
Leave & Time Off Breadth — Paid time off, sick time, holidays, and generous parental leave are provided alongside family medical leave and adoption/fertility assistance. Additional programs like caregiver support and volunteer time off expand the breadth of time-away options.
JPMorganChase Insights
What We Do
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.
Why Work With Us
Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.
Gallery







