Senior Product Analyst

What You'll Do: Define the Measurement System Build the core metric tree from scratch North Star plus the input metrics that move it - for an agentic, self-serve platform. Define activation, adoption, retention, engagement, and expansion metrics that hold up to scrutiny and that PMs actually trust. Establish account/team-level adoption rollups for a B2B, product-led motion.

Own Instrumentation Quality Partner with engineering to design event taxonomies and tracking plans for the full agent lifecycle creation, configuration, testing, deployment, and execution. Audit and close instrumentation gaps so downstream analysis is trustworthy by default.

Analyze Funnels and Friction Map the agent-creation and agent-execution funnels and pinpoint where users stall, abandon, or fail. Turn friction points into prioritized, quantified opportunities for Product and Design.

Measure Value and Outcomes Connect product usage to business outcomes value delivered, cost incurred, and unit economics per agent/execution. Identify which agents, features, and workflows create measurable value, and which quietly don't.

Measure Agent Quality and Feedback Loops Define proxies for task success, output quality, and human-in-the-loop review/override rates. Build the feedback-loop measurement that tells Product and Engineering where agent quality is strong, weak, or degrading and feed it back into the roadmap.

Retention, Expansion, and Risk Signals Define leading indicators of retention, product-led expansion, and churn risk. Surface these signals to Product, Customer Success, and Sales/Solutions so they can act early.

Influence the Roadmap Translate ambiguous product questions into crisp, measurable analysis. Deliver recommendations with clear evidence on what to build, improve, scale, or deprioritize, and make analytics a standing input to prioritization.

Partner Across Functions Work closely with Product, Engineering, Design, Customer Success, Sales/Solutions, and Implementation to make sure the right questions get asked and the answers get used.

Must-Have Skills: 37 years in product analytics for a B2B SaaS or platform product ideally with a self-serve / product-led growth motion. Confident, independent SQL — you write complex queries (cohorting, funnels, window functions) without hand-holding. Hands-on ownership of a product analytics platform — Amplitude, Mixpanel, PostHog, Heap, or equivalent. Demonstrated track record defining product metrics from scratch — activation, retention, engagement, funnels — not just consuming existing dashboards. Experience designing instrumentation and event schemas in partnership with engineering. Ability to translate ambiguous product questions into structured analysis and clear recommendations. Evidence of influencing roadmap or product decisions with data. Strong product judgment and the communication skills to make analysis land with senior stakeholders.

Good-to-Have / Bonus Skills: Experience with AI-native, agentic, LLM, copilot, or workflow-automation products — a strong differentiator, not a requirement. Experience with builder / creation products or developer / no-code / low-code platforms, where measuring how people build things matters. Experience measuring AI output quality, task success, evaluation, or human-in-the-loop review. Unit-economics / cost-per-usage analysis for consumption-priced products. Data modeling (dbt), warehouse experience (Snowflake / BigQuery / Redshift), BI tools (Looker / Metabase / Tableau). Python / pandas for deeper analysis.