Senior Data Scientist Causal Inference & Measurement gesucht in Munich

• Revenue Management & Causal Measurement: You design, develop, and implement sophisticated measurement frameworks focusing on the causal impact of price optimization strategies.
• Causal Inference Modeling: Apply advanced causal inference techniques to guide business decisions and strategy developments in revenue management.
• Experiment Design & Analysis: Develop and refine experimental designs using techniques such as Difference-in-Differences (DiD), Regression Discontinuity Design (RDD), synthetic control methods, A/B tests, and Double Machine Learning to measure effectiveness and inform policy decisions.
• Algorithm & Tool Development: Build and maintain robust algorithms that integrate seamlessly with production systems, ensuring accuracy and scalability in causal estimation.
• Cross-Functional Collaboration: Work closely with product managers, data engineers, and software developers to deploy end-to-end solutions that leverage causal insights to drive business decisions.
• Thought Leadership: Stay current on the latest research in causal inference and measurement, and provide mentorship and guidance to junior team members.

• Industry Experience: You have 5+ years experience in data science with a focus on causal inference, experienced with highly sparse and volatile data and ideally within pricing and/or marketing domains
• Causal Inference Expertise: You have proven track record implementing or optimizing frameworks to measure and validate the impact of revenue management systems and pricing strategies using causal inference techniques
• Technical and Analytical Skills: You have a strong background in statistical analysis and causal inference methods, including but not limited to:
• Double Machine Learning (Double ML): Familiarity with Double/Debiased ML methods that combine machine learning models to estimate causal effects
• Causal Graphs and Structural Causal Models: Proficiency in using Directed Acyclic Graphs (DAGs) for causal identification
• Propensity Score Matching and Weighting: Advanced application of propensity score techniques to estimate treatment effects
• Instrumental Variables (IV) and Synthetic Control Methods: Experience with IV and synthetic controls for causal impact estimation in observational settings
• Difference-in-Differences (DiD) and Regression Discontinuity Design (RDD): Application of DiD and RDD in measuring causal effects over time

• Extra benefits Enjoy discounts on SIXT rent, share, ride and SIXT+, attractive vehicle leasing offers, and exclusive deals with partners for travel, tech, fashion and more

* Mobility boost We support you with a monthly mobility allowance of €20 per month for even more freedom * Future security We contribute to your retirement plan and support you with capital-forming benefits to ensure you are well covered * Feel-good atmosphere Stay active with our modern SIXT gym, various leisure activities like the gaming area or the SIXT choir, and enjoy our high-quality employee restaurant * Flexibility Enjoy 30 days of vacation and a hybrid working model with flexible hours * Giving back Take one day each year to volunteer at a charitable organization dedicated to supporting children Our client is a globally leading mobility service provider with a revenue of €4.00 billion and around 9,000 employees worldwide. Get started with us and apply now!