Top Product Manager Jobs

Reposted 2 Months AgoSaved
Hybrid
5 Locations
101K-205K Annually
Senior level
101K-205K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Own and prioritize features for Capital One's Enterprise Payments platform. Collaborate with designers, engineers, data scientists and stakeholders to define acceptance criteria, break down epics into MVPs, and deliver scalable payment experiences across authorizations, settlement, disputes, backoffice, pricing, and go-to-market. Use data-driven hypotheses and agile practices to drive product adoption and reliability.
Reposted 2 Months AgoSaved
Hybrid
4 Locations
183K-250K Annually
Senior level
183K-250K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Lead product management for the Enterprise Core Platform by applying human-centered design, business-focused strategy, and technology-driven solutions. Drive cross-functional alignment, solve complex problems, and deliver transformative digital products that create long-term value and operational resilience.
Reposted 2 Months AgoSaved
Remote or Hybrid
3 Locations
150K-205K Annually
Mid level
150K-205K Annually
Mid level
Fintech • Machine Learning • Payments • Software • Financial Services
Lead cross-functional teams to define vision and roadmap for Capital One Shopping products. Use SQL/Python/R and data analysis to set and monitor KPIs, troubleshoot issues, and iterate from ideation to production. Partner with analysts, designers, engineers, and stakeholders to launch merchant-focused features that drive revenue and customer value.
Top Skills: AIAi AgentsAPIsBig DataCursorGithub CopilotPythonRSQL
Reposted 2 Months AgoSaved
Hybrid
4 Locations
101K-138K Annually
Senior level
101K-138K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Own and prioritize features for enterprise core platform products. Break down epics into MVP user stories, collaborate with designers, engineers and data scientists, use hypothesis-driven metrics, and drive agile delivery while managing risk and stakeholder communication.
Reposted 2 Months AgoSaved
Hybrid
5 Locations
150K-250K Annually
Senior level
150K-250K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Lead Global Payments Network product efforts to improve consistency, scalability, and adoption of payment experiences. Partner cross-functionally across Authorizations, Settlement, Disputes, Backoffice, Pricing, and Go-to-Market to deliver reliable, efficient consumer-facing digital payment products using data, technology, and collaboration.
Reposted 2 Months AgoSaved
Hybrid
5 Locations
150K-205K Annually
Mid level
150K-205K Annually
Mid level
Fintech • Machine Learning • Payments • Software • Financial Services
Lead product efforts for Global Payments Network to improve consistency, scalability, and adoption of payment experiences. Partner cross-functionally across Authorizations, Settlement, Disputes, Backoffice, Pricing and Go-to-Market, using data and technology to deliver reliable, efficient, customer-centered digital payment products and drive organizational alignment.
Reposted 2 Months AgoSaved
Hybrid
Plano, TX, USA
150K-171K Annually
Mid level
150K-171K Annually
Mid level
Fintech • Machine Learning • Payments • Software • Financial Services
Lead product management for consumer-facing auto products by defining human-centered, technology-driven solutions. Drive strategy translation into digital experiences, lead cross-functional teams, solve complex problems, prioritize business outcomes, and ensure execution excellence across product lifecycle.
Reposted 2 Months AgoSaved
Hybrid
Plano, TX, USA
101K-115K Annually
Senior level
101K-115K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Drive product discovery and delivery for consumer-facing auto-related digital experiences. Break down epics into features and user stories, prioritize roadmaps, collaborate with designers, engineers, and data scientists, use hypothesis-driven assessments, and manage risk while shipping MVPs and scalable product platforms.
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