Senior Product Manager
New
P
PackbackEdTech
Currently we are only able to hire from these states: AL, AR, AZ, CA, CO, CT, FL, GA, HI, IA, IL, IN, KY, MA, MD, MI, NJ, NC, NY, OH, PA, RI, SC, TX, VA, WA, WIFull-TimeSenior
Salary$130,000-$150,000 annually, with an annual bonus target of 15%
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Job Details
- Experience
- 4+ years of product management at a SaaS company
- Required Skills
- SQLProduct ManagementJiraSaaSMarket Research
Requirements
- Have 4+ years of product management experience at a SaaS company.
- Have a track record of taking features or significant enhancements from research through user adoption, with adoption planned beyond launch.
- Have experience in higher education or education more broadly, such as EdTech, institutions, or instruction, and understand what motivates students to do the work.
- Have user research experience, including conducting interviews or building surveys and distinguishing real demand from polite interest.
- Have hands-on AI prototyping experience and be able to explain the problem, learning, and next steps from a prototype.
- Be able to identify weak AI behavior, explain the gap, and propose an effective fix.
- Have experience designing and running experiments and sufficient statistical fluency to interpret results.
- Be comfortable analyzing data with SQL, BigQuery-style analysis, or AI-assisted analysis.
- Understand how software is built and shipped, ask engineers informed questions, and stay curious about systems and data.
- Have experience with an issue tracker such as Jira, Linear, or Azure DevOps and an AI assistant such as Claude or similar.
- Communicate clearly in writing and verbally, and collaborate with engineers and designers.
Responsibilities
- Lead discovery and delivery across multiple product opportunities, from early research through release and user adoption.
- Build business cases, prioritize work, define problems and success criteria, and sequence work into releasable phases.
- Talk regularly with instructors and students to identify demand and track customer, market, and competitor shifts.
- Build working prototypes with AI tools to test ideas before committing engineering time.
- Evaluate AI features for inconsistent, generic, or contextually incorrect output and explain how to improve them.
- Design experiments with clear hypotheses, success and stop criteria, and plans for interpreting results.
- Define outcome metrics and measure impact after release; share findings with the team.
- Align engineering, design, and business stakeholders on product goals and project rationale.
- Partner with sales, customer success, and marketing to communicate product releases and track adoption.
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