We're looking for a Senior Product Manager to start and lead a new team that owns Scout profile data—and the signals built on top of it. Every time a Scout answers a screener or completes a study, their profile learns something new. This team turns that stream of behavior into a living, trustworthy picture of each Scout: their quality, their activity over time, and their fit for the research our customers run.

The Scout profile is the foundation for how we match the right people to the right research. You'll own the signals and scores behind it, including Scout quality, activity, and overall Scout score, along with the work to detect and reduce fraud. You'll also build the evaluation tools that tell us whether those signals are right, and shape how Scout data is structured and used across the platform, so every team building on it can trust what they're getting.

You bring the full PM toolkit—user research, roadmap and strategy, and cross-functional delivery. You pair it with real depth in data, evaluation, and scoring and matching systems, and a hands-on feel for what LLMs can and can't do. You default to ownership: of the roadmap, of outcomes, and of the quality bar that decides whether a score or signal is ready to ship.

Scoring people is different from scoring content. A wrong call has a real cost either way—a great Scout gets overlooked, or a poor match reaches a researcher. You'll make those tradeoffs deliberately, with evidence.

What you'll do

• Build and lead the roadmap and strategy for the Scout profile and the signals built on it, from problem discovery through delivery and iteration
• Define, ship, and evolve Scout signals and scores, including quality, activity over time, and overall Scout scores
• Lead the rearchitecture of how we store, update, and use Scout data, so profiles stay current with every screener, study, and interaction
• Make the Scout profile the core of how we match Scouts to studies, partnering with the teams that own recruiting and matching
• Own the evaluation approach for those systems: build ground-truth sets, measure precision and recall, set thresholds, and know the rollback plan before a change ships
• Partner with Engineering, Data, and Trust and Safety on Scout quality, including detecting and reducing fraud and low-quality participation, and staying ahead of bad actors who adapt
• Specify and prototype quality evaluation tools for internal teams like Research Operations and Support
• Use LLMs directly to extract signals from open-ended responses, prototype ideas, and shape system behavior through prompting and context design
• Decide where deterministic rules, models, and human review each belong, and how that line should move as trust in the system grows
• Treat teams that consume Scout data as customers: understand their workflows, publish clear contracts, and manage downstream impact of changes
• Balance both sides of the marketplace, so changes that improve results for researchers stay fair and clear for Scouts
• Track the metrics that matter: signal accuracy, false-positive and false-negative rates, drift over time, and the effect on study quality and Scout experience
• Partner with Design and Research on tools and experiences that are usable and understandable, not just technically correct
• Mentor other PMs and help raise the bar for evaluation and data thinking across Product

What you bring

• 5–8 years of product management experience, including owning a roadmap end-to-end from strategy through shipped outcomes
• Experience owning data-driven or ML-powered products—such as trust and safety, fraud, risk, recommendations, or scoring systems—and the evaluation decisions behind them
• A strong grasp of evaluation: defining ground truth, choosing metrics, handling imperfect labels, and tuning thresholds with tradeoffs in mind
• Comfort with data modeling and architecture, including event-driven systems, signal provenance, and how structured and unstructured data fit together
• Sound judgment on privacy and responsible data use, including fairness and bias in systems that score people
• A hands-on feel for what different LLMs are good and bad at, and the ability to prototype with that understanding
• Experience partnering with internal teams as customers, and with platform or API consumers
• Experience working in two-sided marketplaces or networks, ideally with a participant or supply-side focus
• A high-ownership mindset: you treat outcomes, not deliverables, as your responsibility
• The influence to align senior stakeholders, make hard calls with incomplete information, and coach other PMs
• Day-to-day fluency with AI tools like Claude, Codex, Cursor, or similar, including personal agents or automated workflows you've built

Nice to have

• Background in data science, analytics, or engineering before moving into product
• Experience building internal tools for operations, support, or review teams
• Experience in B2B, ideally in a market adjacent to UX research, market research, or insights
• Comfort with fast prototypes that get real usage early and then harden into the product, rather than big-spec-first processes

If this role excites you but you're not sure you check every box, we'd still love to hear from you.

Of course, what's outlined above is an ideal set of expectations. Business needs and other projects and tasks may shift, and additional tasks could be assigned at the discretion of your manager.