Senior Data Scientist – Causal Inference
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Job Description
Senior Data Scientist designing experiments and causal models for Muttdata’s data-products and machine-learning startup. Measuring marketing incrementality, attribution, and ROI for a beverage-company engagement in Mexico.
Responsibilities:
- Design, run, and analyze A/B tests and multivariate experiments, including sample size and power calculations, randomization, guardrail metrics, and results interpretation
- 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, including incrementality, attribution, ROI/ROAS, customer lifetime value, and marketing mix modeling
- Translate growth and marketing business questions 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
- Work with marketing, growth, and commercial stakeholders to turn analytical results into decisions driving acquisition, retention, and revenue
- Communicate findings to non-technical audiences
Requirements:
- 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 is nice to have, not required
- Experience in CPG, retail, consumer goods, or beverage industries is nice to have
- Experience with Marketing Mix Modeling and media attribution is nice to have
- Experience with causal libraries and Bayesian modeling is nice to have
- Experience with MLflow and Databricks workflows/jobs is nice to have
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!
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