Product Manager, AI Platform
Job Location:
Job Location:
Columbus, OH - USA
Monthly Salary:
Not Disclosed
Monthly Salary:
Posted on:
30+ days ago
Posted on:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Description
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.
You enjoy shaping the future of product innovation as a hands-on leader driving measurable value for customers guiding successful launches and exceeding expectations. Join a dynamic Corporate & Investment Banking team to build and scale a production entity data platform that enables trusted decisions across front-office workflows risk and controls and AI-driven applications.
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.
Job responsibilities
- 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 products 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.
Required qualifications capabilities and skills
- 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.
Preferred qualifications capabilities and skills
- 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.
Required Experience:
IC
About Company
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans ov ... View more
