Product Manager Jobs at Clipboard Health

Clipboard Health PM interview guide

Clipboard Health runs a case-heavy, writing-first PM loop: roughly 2 written case studies plus 3 to 4 conversations with the team and leadership (often ending with President/COO Bo Lu), and it usually opens with a take-home case before you ever talk to a recruiter. The one thing that defines the loop is that the written cases, not the live chats, are the heaviest signal: they want to see you find a real problem in messy data and write up a sharp, evidence-backed recommendation.

The interview process

1. Take-home case study 1 (Lyft Toledo pricing, multi-hour to multi-day). A written take-home, often sent early, sometimes before a recruiter call. The classic prompt has you act as the pricing PM for Lyft's ride-scheduling launch in Toledo and pick the take rate that maximizes net revenue over 12 months, using supplied data on price, driver pay, match rates, and churn. They grade clarity of writing, data analysis, and whether your recommendation targets a high-effect-size lever.
2. Case review call with a PM (about 30 min). A live walkthrough where you defend your case: how you reached your conclusions, what you assumed, and the tradeoffs you weighed. They probe your reasoning under questioning more than the specific number you landed on.
3. Written case study 2 (Working Backwards / needfinding brief). A second written exercise: either a Working Backwards document for a product scenario in their marketplace, or a Minimum Viable Brief where you interview people in an industry, find a real pain point, and propose a product. Tests needfinding, structure, and crisp written argument.
4. Team and leadership conversations (3 to 4 total). Several conversations with product team members and leadership, frequently ending with the President/COO. Expect culture and judgment probing plus document-based discussion, since the team runs on heavy reading and written feedback.
5. What they're really testing. Clear, concise writing under ambiguity; rigorous data analysis that isolates the highest-effect-size lever; and judgment over polish, meaning they care more about how you reason, label assumptions, and prioritize than the exact answer you reach.

Likely PM interview questions

1. You're the pricing PM for Lyft's ride-scheduling feature launching in a new city like Toledo, Ohio. Given the rider price, driver pay, match rates, and churn data, what take rate (how much Lyft makes per ride) maximizes net revenue on a route over the next 12 months?Execution
2. Only 60 of every 100 requested rides are getting matched with drivers at the current price and driver pay. How would you change pricing to improve the match rate while protecting revenue?Execution
3. If match rates on a route suddenly dropped on the rider side, how would you figure out what happened?Execution