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Product Manager AI; DATA, MDM, UX & Product Roadmap

Job in Santa Clara, Santa Clara County, California, 95053, USA
Listing for: Smart IT Frame LLC
Full Time position
Listed on 2026-07-08
Job specializations:
  • IT/Tech
    AI Business & Operations, Business Systems/ Tech Analyst, Data Analyst
  • Business
    AI Business & Operations, Business Systems/ Tech Analyst, Data Analyst
Salary/Wage Range or Industry Benchmark: 90000 - 130000 USD Yearly USD 90000.00 130000.00 YEAR
Job Description & How to Apply Below
Position: Product Manager with AI (DATA, MDM, UX & PRODUCT ROADMAP

Position:
Product Manager with AI (DATA, MDM, UX & PRODUCT ROADMAP
About the Role

We are looking for an experienced Product Manager with a strong data and Master Data Management (MDM) background to own and drive the end-to-end product experience. From defining the vision and roadmap to delivering intuitive tooling and features, you will work cross-functionally with engineering, design, data, and business stakeholders to build products that are technically excellent, data-driven, and deeply user-centric.

Key Responsibilities
  • Own the product roadmap define, prioritize, and communicate a clear roadmap aligned to business goals, data strategy, and user needs.
  • Lead MDM product strategy drive the vision for master data domains (customer, product, asset, supplier) ensuring data is accurate, consistent, and trusted across the enterprise.
  • Champion UX excellence partner with design to ensure every feature, workflow, and data interface is intuitive, accessible, and impactful for end users.
  • Drive feature development translate user insights, data requirements, and business needs into well-defined epics, user stories, and acceptance criteria.
  • Deliver tooling solutions:
    Identify opportunities to improve data management tooling, reduce manual effort, and increase data quality and productivity across teams.
  • Stakeholder management align cross-functional teams (engineering, design, data, operations) and senior stakeholders on priorities, trade-offs, and delivery timelines.
  • Data-driven decision making use qualitative and quantitative data to validate hypotheses, measure feature success, and continuously improve the product.
  • Discovery & research conduct user research, competitive analysis, and market assessments to inform product strategy and uncover unmet data needs.
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