Jobs at LawnStarter

Lead Product Data Analyst responsible for marketplace modeling, advanced SQL analysis, A/B testing, reporting, dashboard development, metrics governance, and dbt-powered data modeling. The role partners with product managers and stakeholders to turn analysis into business decisions, improve data self-service, document trusted metrics, and nurture a data-driven culture. It is a fully remote individual-contributor position focused on the Pro supply side of the marketplace.

Lead product data analyst responsible for marketplace modeling, advanced SQL analysis, A/B testing, reporting, dashboard trust, and self-service analytics. The role partners with product managers and stakeholders to guide decisions, builds documented dbt datasets, maintains metrics and reports in Lightdash, and supports a data-driven culture. This is an autonomous individual-contributor position focused on the Pro supply side of the marketplace.

Own the growth experimentation program, including test design, power calculations, statistical rigor, monitoring, and readouts across web, SMS, sales, and SEO. Build a trusted acquisition-to-conversion funnel covering CAC, LTV, and conversion rates across channels. Extend automated experimentation tooling using Python, Lightdash, dbt, and AI workflows while partnering with CRO, marketing, and Growth PMs to turn analysis into measurable conversion improvements.

Own marketplace supply and demand dynamics across pricing, pro incentives, supply planning, matching, and service completion. Build forecasting, experimentation, and AI-enabled planning systems across hundreds of markets. Partner cross-functionally with Product, Growth, Finance, and Operations to improve completion rates, customer and pro outcomes, and contribution economics. This fully remote individual contributor role reports to the COO and requires hands-on execution, advanced marketplace expertise, pricing ownership, modeling ability, and elite AI-building skills.

Own the full-cycle recruitment process for US-based Senior and Director-level roles, including sourcing, screening, scheduling, candidate communication, hiring-manager partnership, pipeline reporting, and offer management. The role requires using AI tools and recruiting automations to improve efficiency, managing multiple searches independently, maintaining Workable ATS records, and working remotely from the Philippines with significant US-hours overlap.

Own the growth experimentation program, including test design, power calculations, statistical rigor, readouts, and anytime-valid monitoring. Build a trusted acquisition-to-conversion funnel across paid, organic, and partner channels, incorporating CAC, LTV, and conversion metrics. Extend self-serve experimentation tooling in Lightdash and Python, improve instrumentation with Segment and Flagsmith, automate routine analysis, and influence Growth PM and marketing decisions through clear, statistically sound insights.

Lead distributed teams of 4–5 engineers, owning people development, delivery reliability, team health, cross-functional collaboration, technical direction, and AI workflow adoption. Create growth plans, manage performance and conflict, maintain predictable shipping, surface risks, and partner with Product, Design, Architecture, Quality Engineering, and Security. The role requires remote-native leadership, technical credibility, data-driven management, effective delegation, and hands-on experience driving AI-enabled engineering practices.

Own the company-wide quality engineering vision, testing strategy, CI/CD quality gates, AI-native testing tools, and production quality signals. Lead and mentor the horizontally organized QA squad without initially managing its members. Build and improve unit, component, contract, API, end-to-end, mobile, performance, accessibility, and visual regression testing. Drive quality standards, infrastructure, enablement, and measurable improvements in reliability, pipeline efficiency, and engineering practices.

Staff Software Engineer responsible for leading end-to-end product initiatives, from problem framing and architecture through implementation, production rollout, and metric review. The role partners closely with product managers and designers, uses AI coding agents to accelerate development, and maintains high standards for quality, security, performance, observability, and customer experience. Success is measured by business outcomes, reusable engineering workflows, faster delivery, and production reliability.

Own LawnStarter’s company-wide quality engineering vision, test strategy, CI/CD quality gates, AI-native testing tools, mobile automation, production quality signals, and QA technical mentorship. The role is hands-on across component, contract, API, end-to-end, performance, accessibility, and visual regression testing. It leads QA standards and collaboration without initially managing direct reports, while potentially growing into QA people management.

Staff Product Engineer who owns initiatives end to end, from problem framing and architecture through AI-assisted implementation, production rollout, observability, and post-launch metrics. Partners closely with product managers, designers, and engineering peers while maintaining high standards for quality, security, performance, and customer experience. Builds effective AI-agent workflows, makes autonomous technical decisions, and delivers measurable outcomes in a live marketplace.

Own the end-to-end Service Experience product strategy and roadmap for a two-sided home-services marketplace. Lead AI-powered customer and Pro support, evaluation systems, trust and conflict-resolution policies, and AI-driven experience innovation. Own Contribution LTV and brand-promise metrics, prototype with LLMs, analyze transcripts and data, and influence senior leaders and cross-functional peers without direct reports. Success includes scaling high-quality AI resolution, improving profitability and service outcomes, and delivering an AI experience proof of concept.

Lead distributed teams of 4–5 engineers, owning people development, delivery reliability, team health, cross-functional alignment, technical direction, and AI adoption. Build career growth plans, address performance and conflict directly, manage delivery risks, support architecture decisions, and improve measurable team throughput while maintaining software quality.