Product Manager, AI Analytics & Workflows

Qualifications

• Have 3–5 years of experience in Product Management (or a closely related role) and are comfortable owning execution in ambiguous, high-context environments
• Are strong at writing PRDs and translating real customer workflows into specific, testable product requirements
• Enjoy working with AI/ML and data science teams and can partner effectively
• Are confident defining analytics requirements, including dashboards, metrics, and insight traceability
• Think naturally in terms of measurement and iteration using adoption and workflow metrics to validate impact and prioritize improvements
• Are comfortable working with data and using it to inform product decisions
• Communicate clearly and thoughtfully across technical and non-technical stakeholders, especially when tradeoffs or edge cases matter
• Care deeply about building product experiences that are explainable, reliable, and easy for customers to act on

Responsibilities

• Your mission is to translate customer workflows, data realities, and model-driven outputs into clear product requirements and support high-quality delivery, adoption, and measurable impact across releases
• You’ll partner closely with Engineering, Data Science, Research, and Clinical teams to define requirements for AI-driven workflows, analytics, and reporting experiences, and product-led onboarding
• You will also support release coordination and ensure user-facing documentation reflects the current state of the platform
• This role reports to the VP of Product and Engineering and offers ownership, high cross-functional visibility, and the opportunity to shape how AI is responsibly deployed in clinical and research settings
• Build a strong working understanding of mpathic’s core platform
• Write high-quality PRDs and ship roadmap items by translating customer needs into clear requirements, acceptance criteria, and well-scoped Jira tickets
• Define analytics requirements that help customers measure success and navigate insights
• Partner with Engineering and Data Science to support execution and clarify tradeoffs related to model behavior, edge cases, and product usability
• Improve product-led onboarding by refining in-app guidance, documentation, and workflow education to reduce time-to-value and support adoption
• Support release readiness by coordinating launch communication, release notes, and internal enablement
• Become a trusted owner of high-impact product workstreams across AI-driven workflows, analytics requirements, and onboarding experiences
• Support improvements to how we measure and communicate product quality, especially where data quality and model performance impact customer trust
• Strengthen the platform’s ability to deliver actionable insights through improved traceability, usability, and customer-facing reporting
• Contribute to a team culture that values clarity, strong execution, and building systems that scale across customers and use cases

Full Description

About the position

We’re looking for a Product Manager who thrives in fast-moving, ambiguous environments and wants to have a meaningful impact on shaping AI-powered products that are measurable, trustworthy, and operationally useful.

Your mission is to translate customer workflows, data realities, and model-driven outputs into clear product requirements and support high-quality delivery, adoption, and measurable impact across releases.

You’ll partner closely with Engineering, Data Science, Research, and Clinical teams to define requirements for AI-driven workflows, analytics, and reporting experiences, and product-led onboarding.

You will also support release coordination and ensure user-facing documentation reflects the current state of the platform.

This role reports to the VP of Product and Engineering and offers ownership, high cross-functional visibility, and the opportunity to shape how AI is responsibly deployed in clinical and research settings.

Responsibilities

• Build a strong working understanding of mpathic’s core platform

• Write high-quality PRDs and ship roadmap items by translating customer needs into clear requirements, acceptance criteria, and well-scoped Jira tickets

• Define analytics requirements that help customers measure success and navigate insights

• Partner with Engineering and Data Science to support execution and clarify tradeoffs related to model behavior, edge cases, and product usability

• Improve product-led onboarding by refining in-app guidance, documentation, and workflow education to reduce time-to-value and support adoption

• Support release readiness by coordinating launch communication, release notes, and internal enablement

• Become a trusted owner of high-impact product workstreams across AI-driven workflows, analytics requirements, and onboarding experiences

• Support improvements to how we measure and communicate product quality, especially where data quality and model performance impact customer trust.

• Strengthen the platform’s ability to deliver actionable insights through improved traceability, usability, and customer-facing reporting

• Contribute to a team culture that values clarity, strong execution, and building systems that scale across customers and use cases

Requirements

• Have 3–5 years of experience in Product Management (or a closely related role) and are comfortable owning execution in ambiguous, high-context environments

• Are strong at writing PRDs and translating real customer workflows into specific, testable product requirements

• Enjoy working with AI/ML and data science teams and can partner effectively

• Are confident defining analytics requirements, including dashboards, metrics, and insight traceability

• Think naturally in terms of measurement and iteration using adoption and workflow metrics to validate impact and prioritize improvements

• Are comfortable working with data and using it to inform product decisions

• Communicate clearly and thoughtfully across technical and non-technical stakeholders, especially when tradeoffs or edge cases matter

• Care deeply about building product experiences that are explainable, reliable, and easy for customers to act on