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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'll be a senior individual contributor embedded in the analytics function, driving insights that directly impact business decisions. You'll work closely with product managers, researchers, and business stakeholders to support prioritization, assessments, and strategic recommendations. Unlike a traditional "lead" role, this position carries no direct reports; instead, "Lead" reflects the analytical bar you hold yourself to and your ability to raise standards across the organization.
You'll own three primary areas:
**Modeling & Analysis**: Navigate the complexity of a two-sided marketplace with many moving parts and often contradicting signals. Your work ranges from A/B testing to multivariate retention models, backed by advanced SQL and intermediate Python or R. You'll identify gaps, opportunities, and optimizations that drive business value.
**Reporting**: Build and maintain dashboards and reporting systems that the business trusts. You'll ensure metrics are documented, current, and organized so stakeholders can act on them confidently. A core challenge is unifying metrics across teams so everyone operates from a single source of truth.
**Analytics Engineering**: Occasionally work in the data warehouse using dbt to create clean, documented datasets that power reports and self-serve analytics. SQL is essential; you'll help democratize data access so questions don't require analyst intervention.
Key problems you'll solve include: establishing trusted metrics that eliminate shadow spreadsheets, enabling self-serve analytics so routine questions don't require your involvement, shipping analyses that actually change decisions (not just technically correct answers), and teasing signal from noise in a complex system where supply, demand, pricing, and service quality all interact.
Success in year one means: daily metrics are trusted and documented, routine questions are self-serve, you can name specific decisions your analysis changed, and your dbt models are clean and documented enough for other analysts to build on them.
You'll use AI tools (Claude, ChatGPT, Copilot) daily to move faster—drafting and debugging SQL, scripting analysis, and shaping reports. The role is fully remote with US-facing partners; you're expected to manage your environment and overlap hours. Flexible PTO is measured on outcomes, not hours.
**Requirements:**
- Advanced SQL proficiency and 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 work autonomously and hold yourself to high analytical standards
- Comfort using AI tools daily (Claude, ChatGPT, Copilot, etc.) and willingness to experiment with new capabilities
- Strong learning mindset: ability to understand problems deeply and ask the right questions before reaching for answers
- Business acumen: understanding how metrics connect to product, customers, and financials
- Bias for action: comfort with constraints and scrappy problem-solving; ability to avoid perfectionism
- Excellent communication skills to act as a trusted thought partner with product managers and stakeholders
- English fluency (resume must be in English)
Not a fit if: you're skeptical of AI tools, prefer applying pre-existing processes without learning the business first, want a title and team before raising others' standards, value being right over reaching the right answer together, or prefer analysis disconnected from business decisions.
