Supabase is the Postgres development platform, built by developers for developers.
Provides a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search.
Responsibilities
Own the end-to-end marketing measurement strategy across experimentation, media mix modeling, and attribution for paid and PLG channels.
Establish and evolve the attribution framework: how platform data, multi-touch attribution, MMM, and experiments work together.
Translate complex measurement outputs into clear recommendations on where to invest, what to cut, and how to hit pipeline, revenue, and efficiency targets (CAC, payback, LTV to CAC).
Serve as the subject matter expert for marketing measurement, educating stakeholders on causality, model uncertainty, and limitations.
Design and run always-on incrementality tests, user-level and geo-level, to quantify causal impact.
Calculate incremental lift, incrementality percent, and incremental ROAS/CPA.
Build repeatable analysis templates and playbooks for experiment design, analysis, and readouts.
Partner with channel owners to build and prioritize an experimentation roadmap.
Build and maintain media mix models using historical data to estimate channel contribution, marginal returns, and optimal budget allocation.
Incorporate seasonality, adstock, and saturation effects, and validate model performance through backtesting.
Turn MMM insights into budget scenarios and forecasts across channels and regions.
Own and build the context and skills that let marketing teams run accurate self-serve analytics.
Use AI tools as a core part of daily work to accelerate analysis.
Identify gaps and inconsistencies in marketing data and work cross-functionally to fix them.
Requirements
6+ years in marketing analytics, data science, or a related role, with a focus on performance marketing and/or PLG growth.
Deeply understand marketing attribution, incrementality testing, and media mix modeling.
Advanced in SQL and at least one statistical programming language (Python or R).
Hands-on experience designing, running, and interpreting experiments across digital marketing channels.
Built or worked closely with MMM and/or advanced attribution models.
Strong business acumen and fluency in growth metrics: CAC, LTV, payback period, conversion rates, funnel performance.
Think in terms of self-service and scale.
Can hold technical and strategic context at once.
AI-forward in how you work.
Communicate clearly to non-technical stakeholders.
Thrive in async, autonomous environments.
Nice to Haves
Experience in BaaS, DevRel or open source dev tool companies.
Experience with applied econometrics, time-series modeling, or Bayesian methods.
Familiarity with common marketing and analytics tools (Google Ads, Meta, LinkedIn, web analytics, CDPs, BI/visualization tools).
Conditions
Fully Remote: hire globally, no offices, WeWork membership or co-working allowance.
ESOP: every team member receives equity ownership.
Tech Allowance: budget to set up ideal work environment.
Health Benefits: covers 100% of health insurance for employees and 80% for dependents.