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Est. expiry Sep 8

Senior Data Analyst - Marketing

Marketing Data Analyst

Posted Aug 4 (85 days ago) · Last updated Oct 28

Key facts

Senior marketing analyst, fully remote worldwide; lead experimentation, attribution and media mix modeling.

Where and how
Remote, GlobalRemoteGlobalSenior
Languages required
English
Experience
6 years experience

Original job ad

As published by Supabase

Open the ad
ABOUT SUPABASE Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. ABOUT THE ROLE We're looking for a Senior Data Analyst, Marketing to join our Data Intelligence team and build the measurement foundation that tells us what's actually working across paid and PLG channels. You'll work closely with Marketing, Growth, and channel owners, helping us move past platform-reported metrics and vanity numbers into causal, trusted answers about what drives pipeline and revenue. This role is ideal for someone who thrives in async, fast-paced environments, is AI-forward in how they work, and is excited about building a measurement function from the ground up. WHAT YOU'LL BE RESPONSIBLE FOR Marketing Measurement Strategy - 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 to inform decisions - 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 the limitations of platform-reported metrics Incrementality and Experimentation - Design and run always-on incrementality tests, user-level and geo-level, to quantify the causal impact of key channels, campaigns, and tactics - Calculate incremental lift, incrementality percent, and incremental ROAS/CPA, and use these to guide budget reallocation - Build repeatable analysis templates and playbooks for experiment design, analysis, and readouts so results are consistent across teams - Partner with channel owners (paid search, paid social, lifecycle, website/SEO) to build and prioritize a experimentation roadmap, embedding it into campaign planning, creative testing, and audience strategy 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. ABOUT THE TEAM Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love. - ~400 team members - 60+ countries - 20+ languages spoken - Over $1B raised (including our $500M Series F) - 540,000+ community members We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support—not replace—existing tools and communities.

This is the employer's own ad. Pay, requirements and the other details on this page are our reading of it, not facts the employer confirmed.

About the role

Summarised by JobCrawls from the job ad above.

Requirements

  • At least 6 years of experience in marketing analytics, data science, or a related role, focused on performance marketing and/or PLG growth.
  • Deep understanding of marketing attribution, incrementality testing, and media mix modeling.
  • Advanced SQL and proficiency in Python or R for experiment analysis and modeling.
  • Hands-on experience designing, running, and interpreting digital marketing experiments across search, social, display, email, or in-product channels.
  • Experience building or closely working with MMM or advanced attribution models; consumption or BaaS experience is preferred.
  • Business acumen and fluency in CAC, LTV, payback period, conversion rates, and funnel performance.
  • Ability to build scalable self-service tools and frameworks for marketing teams.
  • Ability to combine technical modeling and strategic business context.
  • Habitual use of LLMs and AI tools, with a considered perspective on their impact on analytics.
  • Clear communication with non-technical stakeholders and ability to explain causal nuance.
  • Ability to thrive in autonomous, asynchronous environments.

Responsibilities

  • Own marketing measurement strategy across experimentation, media mix modeling, and attribution for paid and PLG channels.
  • Develop the framework connecting platform data, multi-touch attribution, MMM, and experiments to decision-making.
  • Turn measurement results into recommendations on investment, cuts, and pipeline, revenue, and efficiency targets.
  • Educate stakeholders on causality, model uncertainty, and platform metric limitations.
  • Design and run ongoing user-level and geographic incrementality tests and use lift, incrementality percentage, and incremental ROAS/CPA to guide budget reallocation.
  • Create reusable experiment design, analysis, and reporting templates and playbooks.
  • Partner with channel owners to develop and prioritize experiments across campaign planning, creative testing, and audience strategy.
  • Build and maintain historical-data media mix models, validate them, and create channel and regional budget scenarios and forecasts.
  • Enable accurate self-service analytics through metric definitions, model documentation, and reusable analysis patterns.
  • Use AI tools in daily analysis and help establish AI-forward marketing practices.
  • Identify and resolve root causes of marketing data gaps and inconsistencies.

Skills & technologies

Marketing AttributionIncrementality TestingMedia Mix ModelingExperiment DesignExperiment AnalysisSQLPythonRStatistical ModelingEconometricsTime-series ModelingBayesian MethodsLLMsGoogle AdsMetaLinkedInWeb AnalyticsCustomer Data PlatformsBusiness IntelligenceData Visualization

Benefits & perks

About Supabase

Supabase logo
Supabase · 40 open roles
Top locations (all time): Remote, Global · 39 · Remote - Global · 13 · Remote, EMEA · 5 · +5 other locations
View company
Current open roles at Supabase on JobCrawls
LocationActive listings
Remote, Global39
Remote - Global13
Remote, EMEA5
Remote, AMER3
Remote, San Francisco, CA1
Europe1
Remote - Anywhere1
Remote1
Current role mix at Supabase on JobCrawls
Role typeActive listings
Software Engineer6
Product Manager5
Platform Engineer4
Engineering Manager3
Support Engineer3
Database Support Engineer2
Performance Engineer2
FinOps Engineer1
Infrastructure Product Manager1
Product Designer1
GRC Analyst1
Cloud Platform Engineer1
People Business Partner1
Brand Designer1
CLI Engineer1
Frontend Engineer1
Deployment Engineer1
Release Engineer1
Developer Relations Engineer1
FinOps Data Engineer1
Technical Program Manager1
FinOps Lead1
Platform Security Engineer1
Pre-Sales Solutions Architect Leader1
Site Reliability Engineer1
Data API Engineer1
Operations Leader1
Distributed Database Engineer1
Partner Solution Architect1
AI Platform Engineer1
Identity and Access Management Engineer1
Engineering Productivity Engineer1
Technical Account Management Leader1
Account Executive1
Marketing Data Analyst1
Postgres Deployment Engineer1
Container Platform Engineer1
Edge Functions Engineer1
Python SDK Engineer1
Technical Partnerships Manager1
Current role-level mix at Supabase on JobCrawls
Role levelActive listings
Senior42
Mid-Level9
Manager4
Director1
Executive1
Expert1
About the employer

Supabase is a developer-built Postgres development platform offering integrated backend services including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. It is remote-first and open-source-first, with approximately 400 team members across more than 60 countries and a community of over 540,000 members.

Core values
Move fastBuild in publicSupport the open-source ecosystem

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