Data Scientist, Causal Inference - Semi Senior (Remote - Worldwide)

Work from anywhere; the team is remote-first. A remote-first data products and machine learning company is looking for a semi-senior data scientist to join a client engagement with a large beverage company in Mexico. The focus is on measuring what truly drives growth and marketing results. You will design experiments and estimate causal impact, then turn those findings into decisions on customer acquisition, retention and revenue. The role suits someone with a quantitative background in economics or a related field who enjoys explaining results to non-technical stakeholders.

What you'll do

• Design, run and analyze A/B tests and multivariate experiments, including power calculations, randomization and guardrail metrics.
• Apply causal inference methods such as difference-in-differences, synthetic control, propensity score matching, instrumental variables, regression discontinuity and uplift modeling to measure campaigns, promotions, pricing and loyalty programs.
• Measure marketing performance through incrementality, attribution, ROI/ROAS, customer lifetime value and marketing mix modeling.
• Turn business questions from marketing, growth and commercial teams into clear analytical problems and experiment designs.
• Build analyses and models on Databricks with Spark and Delta Lake, working with data engineers and analytics engineers on pipelines.
• Develop churn, propensity and segmentation models that support targeting and personalization.

What you need

• At least 3 years of experience in data science, applied statistics, econometrics or a similar analytical role.
• Hands-on Databricks experience (notebooks, PySpark, Delta Lake).
• Solid experience designing and analyzing A/B and other online or offline experiments.
• Strong foundations in statistics and econometrics, including regression, hypothesis testing, time series, and Bayesian and frequentist approaches.
• Proficiency in Python (pandas, PySpark, statsmodels, scikit-learn) and advanced SQL.

Open to applicants anywhere in the world.

How to apply

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