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Supabase

Senior Data Analyst - Marketing

RemoteWorldwide
Published
Role
Data Science
Experience
Senior
Employment
Full-time
Company size
Mid-size
Salary not disclosed
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Open to Worldwide. Set where you work from to check your eligibility.

No BS summary

Senior marketing data analyst with 6+ years in marketing analytics, data science, or related work. Must be advanced in SQL plus Python or R, with hands-on attribution, incrementality testing, media mix modeling, and performance marketing/PLG experience. Fully remote, global role.

Core skills

SQLMedia Mix ModelingMarketing Attribution

Required skills

Python/R

Optional skills

Google AdsMetaLinkedInWeb analyticsCDPsBI/visualization tools

What you'll do

  • 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 across platform data, multi-touch attribution, MMM, and experiments
  • Translate complex measurement outputs into clear recommendations on investment, cuts, pipeline, revenue, and efficiency targets including CAC, payback, and LTV to CAC
  • Serve as the subject matter expert for marketing measurement and educate stakeholders on causality, model uncertainty, and limitations of platform-reported metrics
  • Design and run always-on user-level and geo-level incrementality tests to quantify causal impact of key channels, campaigns, and tactics
  • Calculate incremental lift, incrementality percent, and incremental ROAS/CPA to guide budget reallocation
  • Build repeatable analysis templates and playbooks for experiment design, analysis, and readouts
  • Partner with channel owners across paid search, paid social, lifecycle, and website/SEO to build and prioritize an experimentation roadmap
  • Embed experimentation into campaign planning, creative testing, and audience strategy
  • 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 into models
  • Continuously validate model performance through backtesting and reconciliation with experiment results
  • Turn MMM insights into budget scenarios and forecasts across channels and regions for non-technical stakeholders
  • Own and build context and skills for accurate marketing self-serve analytics, including metric definitions, model documentation, and reusable analysis patterns
  • Use AI tools as a core part of daily work to accelerate analysis and deepen analyst workflow
  • Help establish AI-forward practices across the marketing organization
  • Identify gaps and inconsistencies in marketing data including tracking, spend, and platform exports
  • Work cross-functionally to fix marketing data issues at the root rather than patching downstream

What they require

  • 6+ years in marketing analytics, data science, or a related role, with a focus on performance marketing and/or PLG growth
  • Deep understanding of marketing attribution, incrementality testing, and media mix modeling, and how they complement each other
  • Advanced SQL and at least one statistical programming language, Python or R, for experiment analysis and modeling
  • Hands-on experience designing, running, and interpreting experiments across digital marketing channels including search, social, display, email, and in-product
  • Experience building or working closely with MMM and/or advanced attribution models, ideally in a consumption or BaaS environment
  • Strong business acumen and fluency in growth metrics including CAC, LTV, payback period, conversion rates, and funnel performance
  • Ability to build tools and frameworks that make marketing teams independently capable rather than becoming the bottleneck
  • Ability to hold technical and strategic context at once, from model residuals to budget tradeoffs
  • AI-forward working style with habitual use of LLMs and AI tooling and a clear view on how it changes analyst work
  • Clear communication to non-technical stakeholders and ability to make causal nuance land in business conversations
  • Thrives in async, autonomous environments and is energized by building a measurement function from the ground up
  • Preferred: Experience in BaaS, DevRel, or open source dev tool companies, connecting marketing spend to pipeline and revenue outcomes
  • Preferred: Experience with applied econometrics, time-series modeling, or Bayesian methods for MMM and experimentation

Benefits

  • Fully remote work
  • Global hiring from anywhere
  • WeWork membership or co-working allowance usable anywhere in the world
  • ESOP equity ownership for every team member
  • Tech allowance for laptop, monitor, headphones, or other work environment setup
  • 100% health insurance coverage for employees
  • 80% health insurance coverage for dependents
  • Annual company off-sites in a new city
  • Flexible asynchronous work with trust to manage your own time
  • Annual education allowance for courses, books, conferences, or other professional development

open source backend platform for app development

TechnologyMid-sizesupabase.com

Details

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