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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and analyzing A/B tests and multivariate experiments, applying causal inference techniques, and optimizing marketing performance through advanced statistical methods. Proficient in utilizing Databricks and Python for data analysis and model development to drive business decisions in marketing and growth.
Highest-signal resume keywords
A/B Test Design And AnalysisCausal Inference MethodsDatabricks (Notebooks, Spark, Delta Lake)Python (Pandas, PySpark, Statsmodels, Scikit-learn)Marketing Performance Measurement
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data ScienceApplied StatisticsEconometricsHypothesis TestingRegression AnalysisBayesian ApproachesTime Series AnalysisMarketing Mix ModelingMedia AttributionPredictive Modeling
Soft Skills
CommunicationCollaboration
Tools & Technologies
DatabricksSparkDelta LakeMLflowSQL
Industry Keywords
Consumer GoodsRetailCPGMarketing AnalyticsCustomer Analytics
Tech Stack
Tools & technologiesPandasPySparkPythonScikit-LearnSparkSQL
About the role
Key responsibilities & impact- Design, run, and analyze A/B tests and multivariate experiments, including sample size and power calculations, randomization, guardrail metrics, and results interpretation
- Apply causal inference techniques to estimate the impact of marketing campaigns, promotions, pricing, and loyalty initiatives when randomization is not possible
- Measure and optimize marketing performance, including incrementality, attribution, ROI/ROAS, customer lifetime value, and marketing mix modeling
- Translate growth and marketing business questions into well-defined analytical problems and experimental designs
- Develop analyses, features, and models on Databricks using notebooks, Spark, and Delta Lake
- Collaborate with Data Engineers and Analytics Engineers on data pipelines and analytical datasets
- Build predictive and segmentation models for churn, propensity, customer segmentation, targeting, and personalization
- Work with marketing, growth, and commercial stakeholders to turn analytical results into decisions driving acquisition, retention, and revenue
- Communicate findings to non-technical audiences
Requirements
What you’ll need- 3+ years of experience in Data Science, Applied Statistics, Econometrics, or similar analytical roles
- Hands-on experience with Databricks (notebooks, Spark/PySpark, Delta Lake) – required
- Solid, hands-on experience designing and analyzing A/B tests and online/offline experiments
- Strong knowledge of causal inference methods and their assumptions, limitations, and practical application (DiD, Synthetic Control, Matching, IV, uplift, etc.)
- Strong foundations in statistics and econometrics (hypothesis testing, regression, Bayesian and frequentist approaches, time series)
- Proficiency in Python (pandas, PySpark, statsmodels, scikit-learn) and advanced SQL
- Experience applying data science to growth, marketing, or commercial problems (campaign measurement, pricing, promotions, customer analytics)
- Degree in Economics, Econometrics, Statistics, or related quantitative fields is nice to have, not required
- Experience in CPG, retail, consumer goods, or beverage industries is nice to have
- Experience with Marketing Mix Modeling and media attribution is nice to have
- Experience with causal libraries and Bayesian modeling is nice to have
- Experience with MLflow and Databricks workflows/jobs is nice to have
Benefits
Comp & perks- Remote-first culture – work from anywhere!
- AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
- Birthday off + an extra vacation week (Mutt Week!)
- Referral bonuses – help us grow the team & get rewarded!
- Maslow: Monthly credits to spend in our benefits marketplace
- Annual Mutters' Trip – an unforgettable getaway with the team!