Senior Product Manager, Analytics & AI Insights

CLEAResult

Maryland City (MD)

On-site

USD 103,000 - 155,000

Full time

5 days ago

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Benefits offered by this job

Medical, dental, and vision insurance

401(k) with company match

Paid vacation, sick, personal, and Par

Paid Volunteer Time

Employee Recognition Program

Employee Assistance Program

Access to on-demand training

Job summary

CLEAResult is seeking a Senior Product Manager for Analytics & Insights to own the vision, strategy, and roadmap for client- and program-facing analytics products. You will lead discovery, write PRDs, prioritize the backlog, and partner with Data & AI, Software Engineering, Client Delivery and Success, and program leadership to build AI-enabled analytics.

The role focuses on secure, multi-tenant dashboards, data governance, and scalable branded reporting across clients, with a 1-3 year horizon

Qualifications

5+ years of product management experience, including owning data, analytics, or BI products.
Hands-on experience with the Databricks platform and close collaboration with data engineering teams.
Experience delivering client-facing or embedded analytics in a multi-tenant environment.
Experience with AI-powered products (conversational analytics, LLM-generated insights, or agentic tools).
A record of shipping products with measurable business results.
Experience in a multi-product or platform organization where your product area is one part of a larger solution.
Ability to turn business questions into data requirements and complex data into plain findings for clients.

Responsibilities

Define a 1-3 year vision and an outcomes-focused roadmap for client and program analytics.
Own secure, multi-tenant client dashboards and branded reporting for multiple clients.
Shape how AI makes analytics accessible, with guardrails for accuracy and data access.
Partner with data engineering and platform teams on data ingestion, modeling, governance, and serving.
Work with clients, program managers, and client success teams to validate solutions and communicate roadmap releases.
Coordinate with peer product managers on shared data and integration points across the product ecosystem.
Define and track KPIs like analytics adoption, self-service usage, time to insight, and client satisfaction.
Bring structure to ambiguity using data and feedback to guide decisions.