Senior Data Scientist – Causal Inference & Measurement (m/f/d)

About SIXT

We are a leading global mobility service provider with sales of €3.07 billion and around 9,000 employees worldwide. Our mobility platform ONE combines our products SIXT rent (car rental), SIXT share (car sharing), SIXT ride (cab, driver and chauffeur services), and SIXT+ (car subscription). This platform gives our customers access to our fleet of 222,000 vehicles, the services of 1,500 cooperation partners, and around 1.5 million drivers worldwide. Together with our franchise partners, we are present in more than 110 countries at 2,098 rental stations. At SIXT, a first-class customer experience and outstanding customer service are our top priorities. We focus on true entrepreneurship and long-term stability and align our corporate strategy with foresight.

Want to take off with us and revolutionize the world of mobility? Apply now!

The Role

Join our team of data science and causal inference experts to shape next-generation pricing strategies and measure the causal impact of our initiatives. We employ state-of-the-art causal inference methods to understand and optimize pricing decisions for millions of customers. Our work drives efficient revenue management processes and ensures that our strategies are grounded in robust, scientifically-valid findings.

Job Responsibilities

• Revenue Management & Causal Measurement: Design, develop, and 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 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.

Who You Are

• You have 5+ years in data science with a focus on causal inference, experienced with highly sparse and volatile data and ideally within pricing and/or marketing domains.
• You have a proven track record implementing or optimizing frameworks to measure and validate the impact of revenue management systems and pricing strategies using causal inference techniques.
• You have a strong background in statistical analysis and causal inference methods.

Required Skills and Experience

• Industry Experience: 5+ years 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: 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: 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 and Perks

• Generous Time Off: Enjoy 28 days of vacation, an additional day off for your birthday, and 1 volunteer day per year.
• Work-Life Balance & Flexibility: Benefit from a hybrid working model, flexible working hours, and no dress code.
• Great Employee Benefits: Access discounts on SIXT rent, share, ride, and SIXT+, along with partner discounts.
• Training & Development: Participate in training programs, external conferences, and internal dev & tech talks designed for your personal growth and development.
• Health & Well-being: Private health insurance to support your well-being.
• Additional Perks: Enjoy the Coverflex advantage system to enhance your employee experience.