Senior Data Scientist – Causal Inference

This is a fully remote position, open to applicants in Mexico.

📋 Description

• Design, execute, and evaluate A/B tests and multivariate experiments, encompassing sample size and power calculations, randomization, guardrail metrics, and interpretation of results.

• Utilize causal inference methodologies to assess the effectiveness of marketing campaigns, promotions, pricing strategies, and loyalty programs when randomization is unfeasible.

• Analyze and enhance marketing performance, focusing on incrementality, attribution, ROI/ROAS, customer lifetime value, and marketing mix modeling.

• Convert growth and marketing business inquiries into clearly defined analytical challenges and experimental frameworks.

• Create analyses, features, and models on Databricks using notebooks, Spark, and Delta Lake.

• Collaborate with Data Engineers and Analytics Engineers to develop data pipelines and analytical datasets.

• Construct predictive and segmentation models for churn, propensity, customer segmentation, targeting, and personalization.

• Partner with marketing, growth, and commercial stakeholders to translate analytical insights into actionable decisions that drive acquisition, retention, and revenue growth.

• Present findings to audiences with varying technical backgrounds.

⛳️ Requirements

• Over 3 years of experience in Data Science, Applied Statistics, Econometrics, or related analytical fields.

• Practical experience with Databricks (notebooks, Spark/PySpark, Delta Lake) is essential.

• Strong, hands-on background in designing and analyzing A/B tests and online/offline experiments.

• In-depth understanding of causal inference methodologies, including their assumptions, limitations, and practical applications (e.g., DiD, Synthetic Control, Matching, IV, uplift, etc.).

• Solid foundation in statistics and econometrics, including hypothesis testing, regression, both Bayesian and frequentist approaches, and time series analysis.

• Proficiency in Python (pandas, PySpark, statsmodels, scikit-learn) and advanced SQL skills.

• Experience applying data science to growth, marketing, or commercial challenges, including campaign measurement, pricing, promotions, and customer analytics.

• A degree in Economics, Econometrics, Statistics, or a related quantitative discipline is preferred but not mandatory.

• Familiarity with the CPG, retail, consumer goods, or beverage sectors is advantageous.

• Experience in Marketing Mix Modeling and media attribution is a plus.

• Knowledge of causal libraries and Bayesian modeling is beneficial.

• Experience with MLflow and Databricks workflows/jobs is a plus.

🏝️ Benefits

• 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!