Product Manager, Optimizer

Timely•Boston, MA

2d•$130,000 - $150,000

About The Position

This role is for an experienced product manager who is comfortable operating at the intersection of “hard” algorithmic systems and “soft” customer problems. You'll work together on a product squad with the engineers who build and tune the optimizer. You will own the strategy that brings users from their constraints to optimized schedules, defining the optimization process and experience, validating improvements with customers, and using a blend of AI and UI to ensure the complexity of problem-solving is expressed as simply as possible. This role will balance technical collaboration with product judgment - deciding which optimizer enhancements are worth pursuing, how to measure their effectiveness, and how to design the surrounding experience so that schedulers understand what the optimizer is doing and why. You'll ensure product decisions are clear, priorities are well-communicated, and our roadmap reflects the diverse needs of school schedulers and the demanding needs of a fast-growing business.

Requirements

4+ years in B2B SaaS product organizations, with at least 3 years as a Product Manager.
Experience working on products with an algorithmic, decision-support, or operations research core — you don't need to build the solvers yourself, but you should be comfortable partnering closely with the people who do.
Strong in data analysis and metric design, with the ability to design experiments and interpret their results.
Strong user-centric story writing and mastery of agile toolsets (e.g., Jira, Notion, Miro, etc.).
Demonstrated experience using AI-enabled SDLC practices to streamline the discover-define-build-test-learn loop.
Collaborative by default, detail-oriented problem solver, and a visual communicator (e.g., mockups, sketches, diagrams, journey maps, etc.).

Nice To Haves

Background in EdTech and/or education sector
Experience with optimization, decision-support systems, constraint satisfaction, or algorithmic products
Familiarity with A/B testing or experimentation frameworks
Background in operations research or a technical discipline

Responsibilities

Engage with customers to understand opportunities to generate better K12 school schedules.
Dive deep enough into the optimizer technology and scheduling domain to facilitate critical decisions with our engineering team. Drive those decisions forward with accountability.
Partner with Engineering to surface and refine improvements to the optimizer’s core algorithms, model-builders, and orchestration pipeline to meet user needs.
Collaborate with engineering to design and execute experiments that test optimizer changes, defining consistent performance and quality metrics (e.g., feasibility rate, schedule quality scores, solve time, constraint violations) that determine whether an enhancement is actually working.
Craft optimizer product requirements: defining and refining new product features that are built on (and inspire) new computational capabilities. Work with engineering (and AI agents) to break down requirements into well-defined stories.
Leverage AI to knit together requirements, story definition, and development workflows.
Develop and implement a vision for how generative AI can improve algorithmic optimization of schedules.
Own the end-to-end experience of how school schedulers interact with the optimizer — including how results, tradeoffs, and edge cases like infeasible or sub-optimal solutions are communicated and resolved.
Drive goal- and metric-setting processes with Engineering to motivate and measure optimizer squad outcomes.
Foster a culture of delivering value by setting and adjusting milestones, maintaining high standards, and keeping the team focused on impact.
Communicate product and technology decisions with clarity, ensuring internal and external stakeholders understand priorities and the reasoning behind them.