Senior Data Scientist – Causal Inference

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

📋 Description

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

• Utilize causal inference methods to assess the effects of marketing campaigns, promotions, pricing strategies, and loyalty programs when randomization is not feasible.

• Assess and enhance marketing performance through 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 utilizing notebooks, Spark, and Delta Lake.

• Partner 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.

• Collaborate with stakeholders from marketing, growth, commercial, Data Engineering, and Analytics Engineering.

• Present analytical insights to non-technical audiences.

⛳️ Requirements

• A minimum of 3 years of experience in Data Science, Applied Statistics, Econometrics, or comparable analytical positions.

• Practical experience with Databricks (notebooks, Spark/PySpark, Delta Lake) – mandatory.

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

• In-depth knowledge of causal inference techniques and their assumptions, limitations, and practical applications (DiD, Synthetic Control, Matching, IV, uplift, etc.).

• Solid grounding in statistics and econometrics (hypothesis testing, regression, Bayesian and frequentist methods, time series analysis).

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

• Experience in applying data science to growth, marketing, or commercial challenges (campaign measurement, pricing strategies, promotions, customer analytics).

• A degree in Economics, Econometrics, Statistics, or related quantitative disciplines is a plus.

• Experience in the CPG, retail, consumer goods, or beverage sectors is advantageous.

• Familiarity with Marketing Mix Modeling and media attribution is a plus.

• Experience with causal libraries and Bayesian modeling is preferred.

• Knowledge of MLflow and Databricks workflows/jobs is a plus.

🏝️ Benefits

• Embrace a remote-first culture – work from any location!

• In-house English language lessons.

• Wellhub or sports club stipend to promote physical wellness.

• Comprehensive coverage for AWS, DBT, Google Cloud, Azure & Databricks certifications.

• Food credits available via Pedidos Ya.

• Enjoy a day off for your birthday plus an additional vacation week (Mutt Week! 🏖️).

• Referral bonuses.

• Annual Mutters' Trip.

• Monthly childcare reimbursement.