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Salary: USD 75,000 - 100,000 / annual
LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $150M in annual bookings and two consecutive years of profitability. The company is expanding beyond lawn care to become a one-stop shop for all home services.
You'll join a high-leverage team of Product Data Analysts embedded across the business, owning the semantic layer and the metrics everyone trusts. As a Lead Product Data Analyst, you'll directly impact results through insights and reports, working closely with product managers, researchers, and business stakeholders on prioritization, assessments, and business recommendations.
This is an individual-contributor role—the "Lead" title reflects the analytical bar you hold yourself to and your ability to raise standards for those around you, not people management. You'll work with autonomy, setting your own standards and acting as a trusted thought partner rather than an order-taker.
Key responsibilities include:
**Modeling & Analysis:** Navigate a complex marketplace system with many moving parts and often contradicting signals. Conduct analyses ranging from simple A/B tests to multivariate models on retention or ETA, backed by advanced SQL and intermediate Python or R.
**Reporting:** Create and maintain dashboards and reporting systems that teams trust and can act on. Ensure metrics are organized, documented, and current so stakeholders can self-serve rather than request one-off pulls.
**Analytics Engineering:** Work in the data warehouse to provide clean, documented datasets that power reports and end users. You'll use dbt for transformation, with SQL as a core skill.
You'll focus on the Pro (supply) side of the marketplace, though the exact focus flexes with business needs. Success means trusted metrics, self-serve analytics, analyses that actually change decisions, and clean dbt models that other analysts can build on.
The role solves real problems: untangling conflicting metrics so the business has one number it trusts; ensuring analysis actually moves decisions, not just delivers technically correct answers; building a data-driven culture instead of a bottleneck; and teasing signal from noise in a system where supply, demand, pricing, and service quality all interact.
**Requirements:**
- Daily use of AI tools (Claude, ChatGPT, Copilot, etc.) to move faster on SQL, dbt, scripting, and reporting. This is unlikely to be a good fit if you're skeptical of AI tools or prefer to do everything by hand.
- Deep learning mindset: you ask the right questions before reaching for answers and understand problems thoroughly rather than applying preconceived processes.
- Autonomous work style: you hold your own analysis to a high standard and raise the bar for people around you, functioning as a trusted thought partner, not an order-taker.
- Strong collaboration: you work alongside exceptional people, create an environment where people are excited to work with you, and value reaching the right answer together over being right.
- Business focus: you understand how analysis connects to product, customers, and financials, and can envision how metrics drill down from highest to lowest level.
- Bias for action: you avoid perfectionism and getting tied up in knots, embrace constraints, and enjoy being scrappy.
- Advanced SQL and dbt proficiency required.
- Intermediate Python or R for statistical analysis.
- Experience with BI tools (Lightdash or similar).
- English resume required for application consideration.
