Jobs / United States / Mastercard International Incorporated
Manager, Product Management - Client Data Onboarding, BE&O
Mastercard International Incorporated · 🇺🇸 2 Locations
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 76 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 286 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Mastercard International Incorporated paid sponsored hires in similar roles8 certified filings for “Manager, Product Management” (Data Scientists) in NY: $170k–$179k, median $170k. Most were filed at wage level IV (75%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Mastercard International Incorporated
The US Department of Labor certified 76 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 286 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Mastercard International Incorporated →
About the role
Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Manager, Product Management - Client Data Onboarding, BE&O Manager, Product Management – Client Data Onboarding, BE&O As a member of the Client Data Onboarding Product Management team, you will own and manage our AI-led client data onboarding product. We are rapidly replacing manual ETL with agentic workflows, evolving how we onboard clients in the age of AI, and scaling onboarding across industries and pillars. We are looking for AI-native PMs who can execute and evolve our product strategy and help us build the AI-enhanced version of client data onboarding. This role reports to the Director of Global Product Management within BE&O's Client Data Onboarding team. Position Responsibilities Product Manager for Mastercard's AI-led client data onboarding product, with specific focus on data pipelines, data quality and the onboarding user experience. Partner with Engineering and Data Science leads to define the agentic workflows for data onboarding. Define functional and non-functional requirements for agents, automated data loading, data quality checks and the web app. Keep users in control. Design the human-in-the-loop experience with UX, so that Data Engineers and ACS users can review, edit and approve each agent output, and answer Client Data Requests (CDRs) quickly and with confidence. Develop product strategy derived from user research, client data complexity, onboarding pain points and commercial priorities. Translate a deep understanding of our users and clients into an actionable roadmap. Deliver the early adopter MVP, then scale across R&C industries and FI clients. Own end-to-end feature development. Identify and prioritize problems, define use cases, write requirements and acceptance criteria, support development and end-to-end testing, and measure impact through onboarding time, approval effort, data quality and reduction in manual Data Delivery support. Manage dependencies and delivery risk. Align with the owners of client connectivity, the data ingestion pipeline, Databricks set-up, historical data migration from APT and Data Engineer capacity. Plan interim delivery options where necessary and escalate gaps early. Drive governance and launch readiness. Make sure that responsible AI, security, privacy, data, architecture and BizOps requirements are completed for production, and that PCI/PII data is handled correctly. Work as a part of a cross-functional product team to bring ideas to life. Work together with Engineering, UX, Data Delivery, ACS, the R&C and FI pillars, and C&D to align priorities, client roll-out plans and ownership boundaries. Guide and mentor junior team members through work reviews and sharing of product management practices to foster continuous improvement. All About You Experience working on data and analytics products involving large client datasets, data pipelines, ETL and complex business logic Experience building with AI, LLMs and agents to enhance approaches and/or gain efficiencies, including human-in-the-loop workflows Working knowledge of data modelling, data contracts, semantic layers, data quality and modern data platforms such as Databricks; hands-on data engineering is beneficial but not essential Prior Product Management experience – in product or sim