Lead Product Analyst

Hello, we’re Instrumentl.

Nonprofits do some of the most important work in the world, and most of them are still managing grants in spreadsheets. We’re fixing that. Instrumentl is a profitable, hypergrowth, YC-backed SaaS platform building the operating system for grant-funded organizations. More than 5,500 nonprofits use Instrumentl to discover, track, and win grant funding, from local community organizations to the San Diego Zoo and the University of Alaska.

Collectively they've moved over $1 billion through our platform. We’re doubling year over year, customers love us (NPS 65+, Ellis PMF 60+), and we’re hiring people who want to build something that matters.

The Lead Product Analyst is Instrumentl's first dedicated analytics hire. You will be the sole analyst, building this function from the ground up. Standards, tools, KPIs, experimentation framework: all yours to design.

You’ll spend roughly 60% of your time embedded with our Growth squads (Acquisition + Activation), designing experiments, prioritizing hypotheses, and analyzing what moved the needle. The other 40% goes to building out our semantic layer in Omni and source-of-truth dashboards so PMs, designers, and Sales can self-serve.

You’ll partner with Product, Engineering, and the Data Platform team to make sure experiments are rigorous, data pipelines are accurate, and insights lead to meaningful ARR and efficiency gains. This role reports to our VP of Finance.

• Growth partner. Design experiments, prioritize hypotheses, and analyze what moved the needle in partnership with our Acquisition and Activation Growth squads.
• Experimentation. Own the experimentation framework end-to-end: design, statistical rigor, readouts, and the decisions that come out of them.
• Semantic layer + self-serve. Build out our semantic layer in Omni so PMs, designers, and Sales can self-serve trustworthy answers without pinging you.
• Company reporting. Build source-of-truth dashboards that connect product and growth metrics to ARR, activation, retention, and ROI.
• Data quality. Partner with Engineering and Data Platform to validate tracking, schemas, and pipelines across Heap, Big Query, and Omni.
• Cross‑functional comms. Translate complex analyses into concise, actionable narratives for technical and non‑technical audiences across Product, Growth, and Leadership.

• Founding‑analyst profile. You’ve been the sole analyst or first analytics hire at a smaller company. You’ve built a function from the ground up. Not a specialist who owned one slice at a large org.
• Experience. 5+ years in product, growth, or analytics at a SaaS or PLG company. If you’ve owned analytics end-to-end at a small/mid SaaS company, whether that’s 4 years or 10, we want to talk.
• SQL + BI. Expert SQL (Big Query preferred). Hands‑on with a modern BI tool. We use Omni;
  Looker, Mode, or Tableau experience translates.
• Event tools. Hands‑on with Heap (preferred) or comparable event tools (Amplitude, Mixpanel). You can validate tracking end to end.
• Experimentation chops. Comfortable designing A/B tests, applying statistical rigor, and interpreting results with the right level of certainty.
• Analytical depth. Working knowledge of Python or R for deeper analysis.
• Business orientation. You can connect insights to financial outcomes (activation, conversion, retention) and influence Product and Growth roadmaps.
• Communication. You’re a clear communicator who turns complex analyses into concise, actionable narratives for technical and non‑technical audiences.

• Experience building or scaling a company‑wide experimentation program.
• Exposure to financial or operational analytics such as CAC payback, ROI attribution, or funnel contribution modeling.
• Familiarity with modern data stack tools like dbt, Fivetran, or Airflow.

• Instrumentl has a clear, consistent approach to experimentation and analytics because of this person’s work.
• Growth experiments are measured and communicated with rigor and clarity.
• Funnel insights drive measurable improvements in ARR, activation, and retention.
• Stakeholders trust the data, understand the insights, and act on them…