$ cat jobs/senior-data-scientist-marketing-m-f-d-sixt-76fbbaa329cf.json
Senior Data Scientist - Marketing (m/f/d)
At SIXT, data is at the heart of every smart marketing decision. As part of our Marketing Analytics team, you will work at the intersection of advanced statistical modelling, causal inference, and performance marketing — helping us understand the true impact of our investments and steer budgets more effectively across channels. You will collaborate with marketing stakeholders and cross-functional partners to turn complex model outputs into clear, actionable insights. If you're passionate about using cutting-edge methods to solve real business problems, join Team Orange and apply now. YOUR ROLE AT SIXT 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 YOUR SKILLS MATTER Statistical Modelling & Causal Inference: You have a solid grounding in