Senior Data Analyst, Marketing

TL;DR

Senior Data Analyst, Marketing (Marketing Measurement/Analytics): Building the measurement foundation for paid and product-led growth channels with an accent on attribution, incrementality testing, and media mix modeling. Focus on designing causal experiments, modeling channel contribution and marginal returns, and translating complex analysis into budget and revenue decisions.

Location: Fully remote globally; work from anywhere. Supabase has no offices and supports coworking through a WeWork membership or allowance.

Company

Supabase is an open-source-first Postgres development platform providing integrated database, authentication, storage, edge functions, realtime, and vector search services.

What you will do

• Own the marketing measurement strategy across experimentation, media mix modeling, and attribution for paid and PLG channels.
• Design and run user-level and geo-level incrementality tests, calculating lift, incremental ROAS, and incremental CPA.
• Build and maintain media mix models with seasonality, adstock, saturation effects, backtesting, and budget forecasting.
• Translate measurement outputs into recommendations for channel investment, budget allocation, pipeline, revenue, CAC, payback, and LTV-to-CAC targets.
• Create reusable metric definitions, model documentation, analysis templates, and self-service tooling for marketing teams.
• Partner with channel owners and cross-functional teams to improve experimentation, tracking, spend data, and marketing data integrity.

Requirements

• 6+ years of experience in marketing analytics, data science, or a related field, focused on performance marketing and/or PLG growth.
• Advanced SQL and proficiency in Python or R for experiment analysis and statistical modeling.
• Strong understanding of marketing attribution, incrementality testing, and media mix modeling.
• Hands-on experience designing, running, and interpreting experiments across search, social, display, email, or in-product channels.
• Strong business acumen and fluency in CAC, LTV, payback period, conversion, and funnel metrics.
• Ability to communicate causal analysis and technical uncertainty clearly to non-technical stakeholders in an async, autonomous environment.

Nice to have

• Experience with BaaS, DevRel, open-source developer tools, or consumption-based businesses.
• Applied econometrics, time-series modeling, or Bayesian methods for MMM and experimentation.
• Familiarity with Google Ads, Meta, LinkedIn, web analytics, CDPs, and BI or visualization tools.

Culture & Benefits

• Fully remote, globally distributed work with asynchronous scheduling and flexible time management.
• Employee equity through ESOP.
• Tech allowance for equipment and workspace setup.
• Health insurance coverage for employees and partial coverage for dependents worldwide.
• Annual company off-sites and a professional development allowance.
• Open-source-first culture with a globally distributed team across 60+ countries.