Semi Senior Data Scientist – Databricks, Causal Inference, Growth Marketing

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

📋 Description

• Design, execute, and evaluate A/B tests and multivariate experiments, which include sample size determinations, power calculations, randomization, guardrail metrics, and result interpretations.

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

• Measure and enhance marketing effectiveness through incrementality assessments, attribution analysis, ROI/ROAS calculations, customer lifetime value (CLV) evaluations, and marketing mix modeling (MMM).

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

• Create analyses, features, and models on Databricks utilizing 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 strategies.

• Present analytical insights to marketing, growth, commercial teams, and non-technical stakeholders.

⛳️ 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) is essential.

• Proven experience in designing and analyzing A/B tests and both online and offline experiments.

• Strong understanding of causal inference techniques and their assumptions, limitations, and practical applications (including DiD, Synthetic Control, Matching, IV, uplift, etc.).

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

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

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

• A degree in Economics, Econometrics, Statistics, or related quantitative disciplines, preferably with a focus on applied microeconomics or causal inference.

🏝️ Benefits

• Remote-first work culture – operate from anywhere.

• In-house English language lessons.

• Stipend for Wellhub or sports club membership to promote an active lifestyle.

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

• Meal credits through Pedidos Ya.

• Day off on your birthday plus an additional vacation week (Mutt Week!).

• Referral bonuses available.

• Annual Mutters' Trip.

• Monthly childcare reimbursement.