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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, Python, and SQL for data analysis and model development in marketing and growth contexts.
Highest-signal resume keywords
A/B Testing Design And AnalysisCausal Inference MethodsDatabricks (Notebooks, Spark, Delta Lake)Python (Pandas, PySpark, Statsmodels, Scikit-learn)Marketing Mix Modeling
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 AnalysisIncrementality MeasurementAttribution AnalysisCustomer Lifetime Value
Soft Skills
CommunicationCollaboration
Tools & Technologies
DatabricksSparkDelta LakeMLflowSQL
Industry Keywords
Consumer Packaged GoodsRetailMarketing AnalyticsCampaign MeasurementPromotions
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 interpretation of results
- 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 through 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, commercial, Data Engineering, and Analytics Engineering stakeholders
- Communicate analytical 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
- 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!
- In-Company English Lessons.
- Wellhub or sports club stipend to stay active
- AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
- Food credits via Pedidos Ya
- Birthday off + an extra vacation week (Mutt Week! 🏖️)
- Referral bonuses
- Annual Mutters' Trip
- Monthly Childcare Reimbursement