Media Mix Modeling and Forecasting

• 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 continuously validate model performance through backtesting and reconciliation with experiment results
• Turn MMM insights into budget scenarios and forecasts across channels and regions, communicated in a way non-technical stakeholders can act on

Context, Tooling, and Data Integrity

• Own and build the context and skills that let marketing teams run accurate self-serve analytics: metric definitions, model documentation, and reusable analysis patterns, not just dashboards
• Use AI tools as a core part of daily work to accelerate analysis and go deeper than a traditional analyst workflow allows, and help establish AI-forward practices across the marketing org
• Identify gaps and inconsistencies in marketing data (tracking, spend, platform exports) and work cross-functionally to fix them at the root rather than patching around them downstream

You Might Be a Good Fit If You Have

• 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, and how they complement each other rather than compete
• Are advanced in SQL and at least one statistical programming language (Python or R) for experiment analysis and modeling
• Have hands-on experience designing, running, and interpreting experiments across digital marketing channels: search, social, display, email, in-product
• Have built or worked closely with MMM and/or advanced attribution models, ideally in a consumption or BaaS environment
• Have strong business acumen and fluency in growth metrics: CAC, LTV, payback period, conversion rates, funnel performance
• Think in terms of self-service and scale: your instinct is to build tools and frameworks that make marketing teams independently capable, not to become the bottleneck for every "did this work" question
• Can hold technical and strategic context at once: you're as comfortable in a model's residuals as you are in a conversation about budget tradeoffs
• Are AI-forward in how you work: you use LLMs and AI tooling habitually and have a clear point of view on how it changes what an analyst can do
• Communicate clearly to non-technical stakeholders and know how to make causal nuance land in a business conversation
• Thrive in async, autonomous environments and are energized by building a measurement function from the ground up

Nice to Haves

• Experience in BaaS, DevRel or open source dev tool companies, connecting marketing spend to pipeline and revenue outcomes
• Experience with applied econometrics, time-series modeling, or Bayesian methods for MMM and experimentation
• Familiarity with common marketing and analytics tools (Google Ads, Meta, LinkedIn, web analytics, CDPs, BI/visualization tools)

What We Offer

• Fully Remote: We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world.
• ESOP: Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together.
• Tech Allowance: Use this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work.
• Health Benefits: Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us.
• Annual Off-Sites: Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year.
• Flexible Work: We operate asynchronously and trust you to manage your own time. You know what needs to be done and when.
• Professional Development: Every team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth.