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Senior Data Scientist, Marketing

Dropbox
Remote - US: Select locationsApr 10, 2026·Posted 1 day ago
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Domain

Tech Stack

SQLHadoopPythonRGeoliftCausal ImpactMeridianLightweight MMMRobynClaude CodeGPT CodexCopilot

Must-Have Requirements

  • Bachelor's degree in quantitative discipline (Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field)
  • 7+ years of analytics experience driving key business decisions
  • Proficiency in SQL and large unstructured datasets such as Hadoop
  • Deep understanding of statistical analysis, experimentation design, and analytical techniques like regression, decision trees
  • Solid background in running multivariate experiments
  • Strong verbal and written communication skills
  • Proficiency in programming/scripting (Python or R)

Nice to Have

  • -Experience with open source packages for incrementality tests (Meta's Geolift, Google's Causal Impact)
  • -Experience with MMM packages (Google's Meridian, Lightweight MMM, Meta's Robyn)
  • -Master's or Ph.D. in quantitative field
  • -Experience with predictive modeling, machine learning, and experimentation/causal inference methods
  • -Experience using AI coding assistants (Claude Code, GPT Codex, Copilot)

Description

Role Description We're looking for a Senior Data Scientist to partner with Marketing, Brand, Product and Finance teams to answer key questions about the effectiveness of marketing across all our paid and owned channels. We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights. An ideal candidate should have robust knowledge of marketing measurement methods (eg. causal inference, attribution, MMM) and strong technical fluency in scripting (Python/R) and querying (SQL) .

Responsibilities

Evaluate and improve our marketing measurement leveraging techniques such as MMM(Marketing Mix Modeling), MTA(Multi touch attribution) and incrementality testing Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends. Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments Translate complex concepts into implications for the business via excellent communication skills, both verbal and written Understand what matters most and prioritize ruthlessly Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field 7+ years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting Proven track record of being able to work independently and proactively engage with business stakeholders with minimal direction Significant experience with SQL and large unstructured datasets such as Hadoop Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees Solid background in running multivariate experiments to optimize a product or revenue flow Strong verbal and written communication skills Proficiency in programming/scripting and knowledge of statistical packages like R or Python

Preferred Qualifications

Experience in using open source packages for incrementality tests(e.g. Meta’s Geolift, Google’s Causal Impact) and MMM (Google’s Meridian, Lightweight MMM or Meta’s Robyn) Master's or Ph.D. Degree in a quantitative field Experience with predictive modeling, machine learning, and experimentation/causal inference methods. Experience using AI coding assistants (e.g., Claude Code, GPT Codex, Copilot, or similar tools) Compensation US Zone 1 This role is not available in Zone 1 US Zone 2 $173,700 —

$234,900 USD

US Zone 3 $154,400 —

$208,800 USD