Product Owner

Description Who We Are:

Dedicated to making a difference in law enforcement agencies across the U.S., our mission is to transform policing by elevating officer performance with a preventative-based early intervention system. Driven by data science and powered by machine learning, our offering analyzes officer performance data in order to identify potentially problematic behavior. In partnership with the University of Chicago, we’ve developed the world’s largest multi-jurisdictional officer performance database, and the only research-driven, evidence-based early intervention system available in policing today.

We’re also the only provider of a fully integrated, cloud-based Software-as-a-Service (SaaS) platform that simplifies essential policing workflows. This platform is designed to be a single-source solution for all operational needs, driving extensive efficiency gains and providing best-in-class advanced analytics and insights.

Benchmark Analytics provides a comprehensive, all-in-one solution that is advancing police force management through state-of-the-art technology and market-leading data and analytics.

The Role We are looking for a Product Owner who will take full ownership of a defined product surface within our platform — whether that is shared infrastructure, a new product being built from scratch, a specialized law enforcement workflow, or a data-driven analytics experience. You will work as a trio alongside a lead engineer and a junior engineer, using our AI-augmented software development lifecycle to deliver at a pace that traditionally required much larger teams. This is not a traditional product manager role: you own scope, priority, and delivery accountability in one seat, and you produce complete, engineering-ready specifications that your engineering pair can build from directly.

Responsibilities

• Own your product surface end to end — deciding what gets built, when it ships, and how it serves your users or consuming teams, with full accountability for scope, priority, and quality
• Produce engineering-ready specifications for all features — complete user flows, visual designs, data requirements, edge cases, and acceptance criteria — using AI tools as a core part of your workflow; engineering builds from your specifications directly, without ambiguity about what the experience should be
• Make priority decisions and defend them — customer success, sales, and leadership will bring you requests; you decide which enter the roadmap and which don’t, with clear reasoning and transparent communication
• Maintain deep fluency with your customers — whether they are law enforcement practitioners, agency administrators, internal platform consumers, or data science teams — through direct engagement, user research, and ongoing relationship-building
• Conduct or commission user research as needed — interviews, usability testing, workflow observation, product analytics review — and engage internal subject matter experts to ground product decisions in direct evidence rather than assumptions
• Partner directly with your engineering pair as a trio; bring clarity on what to build and why while they bring clarity on how to build it and what is feasible
• Own post-launch adoption and feedback — evangelize new capabilities, train internal teams, track feature adoption, gather user feedback, maintain documentation, and iterate based on real-world usage rather than handing off after launch
• Support enterprise sales conversations with substantive product and domain knowledge when needed — not just feature lists, but the depth that builds customer confidence
• Leverage AI tools and technologies across all aspects of your work — research, specification, design, analysis, prototyping, and documentation

Requirements Job Qualifications:

• 5+ years of professional experience in product management, technical product management, engineering, design, or another role where you owned both the what and the how of a product or technical surface
• Demonstrated ability to produce engineering-ready specifications — not just PRDs or user stories, but complete specifications including visual designs, user flows, data requirements, and acceptance criteria that engineering can build from directly
• Fluency with AI-assisted workflows; you already use AI tools daily in your professional work and can demonstrate how they accelerate your output and raise the quality of your work
• Strong …