Join a team of data science and causal inference experts to shape next-generation pricing strategies and measure the causal impact of initiatives in Pullach near Munich! We employ state-of-the-art causal inference methods to understand and optimize pricing decisions for millions of customers. Our work not only drives efficient revenue management processes but also ensures that our strategies are grounded in robust, scientifically-valid findings.

Aufgaben

• 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.

Qualifikation

• 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

Benefits

• 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!

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