Staff Data Analyst

Your Mission

We are looking for a Staff Growth Data Analyst to join our Data organization and support our Marketing, Growth, and Product teams. This person will help us better understand how customers discover, evaluate, activate, convert, retain, and expand on our platform and how our marketing investments, product-led growth motions, and experimentation programs translate into sign-ups, revenue growth, and long-term customer value.

This is a high-impact role for someone with deep experience across growth analytics, marketing analytics, product-led growth, and experimentation. You will partner closely with Marketing, Growth, Product, Finance, Engineering, and Data teams to measure performance, optimize acquisition and conversion, evaluate PLG initiatives, and identify the drivers of sustainable growth.

The ideal candidate is highly analytical, technically strong, and comfortable operating in ambiguous, fast-moving environments. You should be able to go deep in SQL and data modeling, build scalable reporting and measurement frameworks, design and analyze experiments, and translate complex data into clear recommendations for business leaders.

What You’ll Do

• Lead analytics across marketing acquisition, product-led growth, lifecycle growth, and channel performance, spanning paid, organic, lifecycle, partnership, affiliate, referral, and in-product channels.
• Own analysis of the full growth funnel, including acquisition, activation, onboarding, conversion, retention, monetization, expansion, and long-term customer value.
• Develop and improve attribution, campaign measurement, and marketing efficiency frameworks to help the business understand what is driving sign-ups, revenue, CAC, ROAS, LTV, and payback.
• Lead experimentation analytics across the growth funnel, including A/B tests, incrementality tests, onboarding experiments, landing page tests, lifecycle experiments, pricing/packaging tests, and in-product conversion tests.
• Design and evaluate experiments end to end, including hypothesis development, metric selection, test sizing, statistical interpretation, readouts, and rollout recommendations.
• Build dashboards, reporting frameworks, and analytical models that give teams clear visibility into performance across campaigns, channels, segments, cohorts, funnels, and experiments.
• Analyze customer journeys using campaign data, UTM parameters, product usage data, conversion events, lifecycle touchpoints, and marketing schemas to improve tracking quality and uncover growth opportunities.
• Develop or support advanced analyses such as LTV modeling, customer segmentation, propensity modeling, churn analysis, product-qualified lead scoring, and upsell/cross-sell opportunity analysis.
• Partner with Data Engineering and Analytics Engineering to improve data quality, event instrumentation, marketing/product data models, and self-service reporting infrastructure.
• Communicate insights, tradeoffs, experiment results, and recommendations clearly to Marketing, Growth, Product, Finance, and executive stakeholders.

What You’ll Bring

Required

• 7+ years of experience in growth analytics, marketing analytics, product analytics, business analytics, data science, or a related analytical role.
• Strong experience supporting Marketing, Growth, Acquisition, Revenue, or Product teams in a high-growth business environment.
• Experience with product-led growth motions, including self-serve funnels, activation, onboarding, free-to-paid conversion, product-qualified leads, retention, and expansion.
• Deep hands-on experience with experimentation, including A/B testing, experiment design, statistical analysis, incrementality measurement, funnel experimentation, and translating results into business recommendations.
• Hands-on experience with attribution modeling, campaign measurement, UTM tracking, conversion analysis, and marketing performance metrics such as CAC, LTV, ROAS, conversion rate, churn, retention, and payback period.
• Strong SQL skills and experience working with large, complex datasets, ideally in Snowflake or a similar cloud data warehouse.
• Experience with BI tools such as Looker, Tableau, Power BI, or similar platforms.
• Strong business judgment, communication skills, and ability to connect analytical work to customer growth, revenue, margin, efficiency, retention, and long-term business performance.
• Experience working cross-functionally with marketing, data, product, engineering, and finance teams.

Preferred

• Experience with Marketing Mix Modeling / Media Mix Modeling.
• Experience with marketing, product analytics, and experimentation platforms such as Google Analytics, Amplitude, Mixpanel, Optimizely, Statsig, Eppo, LaunchDarkly, Google Ads, Meta Ads Manager, or similar tools.
• Experience with dbt, modern analytics engineering workflows, and cloud data environments.
• Experience with Python or R for advanced analysis, modeling, automation, experimentation analysis, or statistical work.
• Experience with customer segmentation, cohort analysis, LTV modeling, propensity modeling, churn modeling, causal inference, lift studies, or product-qualified lead scoring.
• Experience working in a PLG, self-serve SaaS, marketplace, travel, fintech, e-commerce, or other high-transaction-volume growth environment.