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# Senior Data Scientist - Marketing

- **Company:** Sixt
- **Location:** Lisbon, OH, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Airflow, Amazon Web Services, Big Data, Bing Ads, Cloud Computing, Database Queries, Programming Tools, Python (Programming Language), Machine Learning, NumPy, SQL Databases, Workflow Management Systems, Google Search, Model Validation, Pandas, Matplotlib, Scikit Learn, Plotly, Streamlit Framework
- **Published:** July 22, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/p6l8yqudwv

## About the Role

* Statistical Modelling & Causal Inference You have a solid grounding in Bayesian methods, causal inference (e.g. DiD, Interrupted Time Series, BSTS), and quasi-experimental design; familiarity with PyMC or comparable probabilistic programming tools is a strong plus
 * Python & Data Stack You are proficient in Python with hands-on experience using Pandas, NumPy, Scikit-learn, and visualisation libraries such as Matplotlib and Plotly, comfortable working in both notebooks and production codebases
 * SQL & Cloud Infrastructure You bring strong SQL skills and practical experience querying large datasets in AWS environments, ideally using Athena or Redshift; familiarity with Airflow or similar orchestration tools is a plus
 * Machine Learning You have a solid understanding of supervised and unsupervised ML techniques, model evaluation, and how to take a model from experimentation to a reliable, maintainable production output
 * Online Marketing Knowledge You are familiar with paid search and/or display advertising - including how campaign structures work, what tROAS and tCPA mean in practice, and how performance marketing metrics connect to business outcomes
 * Communication & Collaboration You can translate complex model outputs into clear, actionable narratives for marketing and business stakeholders; experience with Streamlit or a comparable dashboarding tool, as well as GenAI-assisted development approaches such as Spec-Driven Development, is a plus

## Description

* You uncover the true incremental impact of marketing investments using experimental and quasi-experimental methods - including Difference-in-Differences, Interrupted Time Series, and Bayesian Structural Time Series - to establish causal evidence where traditional A/B tests are impractical or unavailable
 * You develop and maintain proprietary response-curve and elasticity models to reduce reliance on platform-native estimates and support better budget allocation decisions across channels and campaign types
 * You support the development and maintenance of a Marketing Mix Model (MMM), contributing to model specification, prior elicitation, and validation, and translating outputs into actionable budget allocation recommendations
 * You help extend the team's bid-target steering framework beyond Google Search Ads to channels such as Display, Meta, and Bing Ads, adapting modelling approaches to each channel's measurement and data characteristics
 * You explore and evaluate data-driven attribution approaches, using web behavioural data to understand the customer journey and benchmark against existing third-party attribution
 * You present model findings clearly to marketing and cross-functional stakeholders, contributing to internal dashboards and Streamlit applications that operationalise your work


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