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CircleCI

Marketing Data Scientist

CircleCI

Marketing Data Scientist at CircleCI analyzing marketing data and building models for business decisions. Collaborating with marketing teams to enhance customer growth strategies.

Posted 6/11/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSenior💰 $145,000 - $196,000 per yearWebsite

Tech Stack

Tools & technologies
ETLPandasPythonScikit-LearnSQL

About the role

Key responsibilities & impact
  • Frame ambiguous marketing problems as well-scoped modeling and measurement challenges and own them end to end.
  • Develop and own attribution models that accurately allocate marketing investment across channels and touchpoints.
  • Build propensity, lead scoring, and churn models to prioritize where GTM teams should focus.
  • Model the relationship between product engagement signals and downstream commercial outcomes — expansion, retention, and conversion.
  • Design, execute, and interpret experiments (A/B, MVT, geo-based) with appropriate power analysis and statistical validity.
  • Build and apply segmentation models and cohort analyses to uncover behavioral patterns, lifecycle trends, and funnel opportunities.
  • Analyze organic search and AEO signals as modeling inputs to inform content strategy and improve discoverability.
  • Partner with analytics engineers to productionize models and move insights from notebook to pipeline.
  • Use AI tools to move faster, explore unfamiliar methods, and surface modeling options — while developing the judgment to know when AI-generated outputs are wrong or incomplete.

Requirements

What you’ll need
  • Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, Economics, or a related quantitative field; Master's or PhD is a bonus.
  • 4 to 6 years applying data science in a product, growth, or marketing context at a high-growth company.
  • Strong command of Python (pandas, scikit-learn, statsmodels, or similar) and analytical SQL.
  • Demonstrated experience building predictive models that influenced real business decisions.
  • Hands-on experience with marketing measurement — attribution, media mix modeling, incrementality testing, or similar.
  • Solid statistical foundation — forecasting, regression, classification, causal inference, and experiment design.
  • Experience with GA4, Google Ads, and digital marketing measurement platforms.
  • Strong understanding of reverse ETL processes and operationalizing model outputs.
  • Strong storytelling skills — able to translate statistical complexity into clear, actionable business language for both technical and non-technical audiences.

Benefits

Comp & perks
  • Reasonable accommodation for individuals with disabilities

ATS Keywords

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Hard Skills & Tools
Pythonpandasscikit-learnstatsmodelsanalytical SQLpredictive modelingmarketing measurementattribution modelingexperiment designstatistical analysis
Soft Skills
storytellingcommunicationanalytical thinkingproblem-solvingcollaboration
Certifications
Bachelor's degreeMaster's degreePhD