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

MUTT DATA

. Design, run, and analyze A/B tests and multivariate experiments, including sample size and power calculations, randomization, guardrail metrics, and interpretation of results .

Posted 10/7/2026full-timeRemote • ArgentinaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and analyzing A/B tests and multivariate experiments, applying causal inference techniques, and utilizing advanced data science tools like Databricks and Python for marketing performance optimization. Strong analytical skills in statistics and econometrics are essential for translating business questions into actionable insights.

Highest-signal resume keywords

A/B Test Design and AnalysisCausal Inference TechniquesDatabricks (Notebooks, Spark, Delta Lake)Python (Pandas, PySpark, Statsmodels, Scikit-learn)Advanced SQL

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Hard Skills

A/B Test DesignCausal InferenceStatisticsEconometricsData SciencePredictive ModelingSegmentation ModelsMarketing Mix ModelingIncrementality MeasurementAttribution Analysis

Soft Skills

CommunicationCollaborationAnalytical Thinking

Tools & Technologies

DatabricksSparkDelta LakePythonSQL

Industry Keywords

Marketing PerformanceCustomer AnalyticsCampaign MeasurementPromotionsLoyalty Initiatives

Tech Stack

Tools & technologies

PandasPySparkPythonScikit-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 (CLV), and marketing mix modeling (MMM)
Translate business questions from growth and marketing teams 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 strategies
Communicate analytical findings to marketing, growth, commercial, and non-technical stakeholders

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 (ideally with a focus on applied microeconomics or causal inference)

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