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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 and is investing in the next generation of its platform.
As a Lead Product Data Analyst, you will directly impact business results through insights and reports. You'll work closely with product managers, researchers, and business stakeholders to support prioritization, assessments, and business recommendations. You'll help nurture a data-driven culture across the company by making data easier to consume through interactive reports, datasets, documentation, and training.
This is an autonomous individual-contributor role focused on the Pro (supply) side of the marketplace, though priorities flex with business needs. The "Lead" title reflects the analytical bar you hold yourself to and your role as a trusted thought partner—not a people-management position.
Key responsibilities include:
**Modeling & Analysis:** Navigate the complexity of a two-sided marketplace with many moving parts and contradicting signals. Conduct analyses ranging from A/B tests to multivariate models on retention or ETA, using advanced SQL and intermediate Python or R.
**Reporting:** Understand team needs and create/maintain reporting systems that are organized, trustworthy, and actionable. Ensure metrics are current and correct, eliminating shadow spreadsheets and conflicting numbers across teams.
**Analytics Engineering:** Work in the data warehouse to provide clean, documented datasets that power reports and self-serve analytics. You'll use dbt for transformation, with SQL as a core skill.
Key problems you'll solve: untangling conflicting metrics so the business has one trusted number; ensuring analysis actually drives decisions, not just delivers technically correct answers; building self-serve data access so stakeholders don't need to file tickets; and teasing out signal from noise in a system with many interacting variables (supply, demand, pricing, service quality).
Success in Year 1 means: trusted, documented, current metrics that eliminate shadow spreadsheets; routine questions becoming self-serve; specific decisions your analysis changed; and clean, documented dbt models that other analysts build on without redoing your work.
You are AI-native, using Claude, ChatGPT, Copilot, and similar tools daily to move faster on SQL, dbt, scripting, and reporting. You have a learning mindset, taking pride in understanding problems deeply before reaching for answers. You set the bar through autonomous work and raise standards for those around you. You're a team player who values intellectual honesty and trust. You care deeply about business needs and how analysis connects to product, customers, and financials. You have a bias for action and embrace constraints rather than perfectionism.
This role is NOT a ticket queue, a dashboard-admin seat, a people-management role, or one that waits for perfectly clean data.
**Requirements:**
- Advanced SQL proficiency
- Intermediate Python or R for statistical analysis
- Experience with dbt for data transformation and modeling
- Familiarity with BI tools (Lightdash or similar)
- Demonstrated ability to translate business problems into analytical questions
- Experience in a data-driven organization or marketplace environment (preferred)
- Comfort with AI tools and willingness to experiment with new capabilities
- Strong communication skills to translate technical findings for non-technical stakeholders
- English fluency (resume must be in English)
