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Lead Data Analyst, Growth & Experimentation

🔥 14 hours ago

🌐 Brazil, Mexico, +1 more countries – Remote

infoinfo

💵 $75k - $100k / year

⏰ Full Time

🟠 Senior

📉 Data Analyst

Where this job comes from

Posted on LawnStarter's careers page, not through a job board

First seen by Remote Rocketship 14 hours ago

Still open on LawnStarter's site. Checked 3 hours ago.

Logo of LawnStarter

LawnStarter

51 - 200 employees

Founded 2013

👥 B2C

🏪 Marketplace

🏠 Real Estate

💰 $10.5M Venture Round on 2019-11

B2C • Marketplace • Real Estate

LawnStarter is a service platform that provides affordable lawn care services at the click of a button. With fast online ordering, quality service, and a user-friendly app, LawnStarter allows customers to easily schedule and manage lawn maintenance services. These include lawn mowing, fertilization, bush trimming, and weeding. The company partners with local professionals to ensure reliable and insured services while supporting small businesses. LawnStarter offers its services across numerous locations in the United States, aiding customers in keeping their lawns beautiful and well-maintained.

📋 Description

• Own the experimentation program across web funnels, SMS/drip, sales-driven tests, and SEO tests • Design experiments and make power, sample-size, significance, and readout-standard decisions • Catch underpowered tests, false positives, tracking issues, and attribution problems • Extend anytime-valid monitoring, automated health checks, Lightdash metrics, Python statistical tooling, and AI skills • Build a trusted acquisition-to-conversion funnel model across brands and channels • Provide CAC, LTV, and conversion-rate analyses for Growth investment prioritization • Develop the Growth analytics standards and playbook by the end of Year 1 • Recommend whether to buy or build the experimentation stack • Partner with the Director of CRO, performance marketing, Growth PMs, and the CEO • Deliver insights that drive quantified conversion improvements

🎯 Requirements

• Expertise in SQL • Enough Python to automate statistical-significance calculations • Comfort with dbt and Lightdash • Ability to build data models independently without waiting on data engineering • Daily use of AI for SQL, dbt, and analysis pressure-testing • Experience with experiment design, power, significance, novelty effects, and interaction effects • Knowledge of Segment events and Flagsmith randomization • Understanding of CAC, LTV, attribution, seasonality, and channel mix • Ability to explain broken experiments in plain terms • Ability to influence PMs and marketers without formal authority • Ability to work with acquisition-to-conversion funnels across paid, organic, and partner channels

🏖️ Benefits

• AI tooling provided: Claude routines already running pieces of the experimentation process • Fully remote work • Flexible PTO measured on outcomes, not hours logged • Scope as the first analyst dedicated entirely to Growth and Experimentation

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