Lead Data Analyst, Growth & Experimentation

LawnStarter

. Own the experimentation program across web funnels, SMS/drip, sales-driven tests, and SEO tests .

Posted 10/30/2026full-timeRemote • Brazil, Mexico, ColombiaSenior💰 $75,000 - $100,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in SQL and Python for statistical analysis and experiment design, with a strong focus on building data models and optimizing acquisition-to-conversion funnels. Proficient in utilizing AI tools for data analysis and delivering actionable insights to drive conversion improvements.

Highest-signal resume keywords

SQL ExpertisePython AutomationExperiment DesignCAC and LTV AnalysisLightdash Proficiency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonExperiment DesignStatistical AnalysisData ModelingCAC AnalysisLTV AnalysisAttribution UnderstandingSignificance TestingChannel Mix Knowledge

Soft Skills

Influencing Without AuthorityClear Communication

Tools & Technologies

DbtLightdashAI ToolsSegmentFlagsmith

Industry Keywords

Acquisition-to-Conversion FunnelGrowth AnalyticsPerformance MarketingExperimentation ProgramConversion Rate Optimization

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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