We believe in connecting great people with great opportunities.
Our team is currently recruiting for a client in Germany, and we would be delighted to have you explore this opening.
Tasks
Designed and implemented advanced frameworks to measure the causal effects of pricing and revenue optimization initiatives.
Applied cutting-edge causal inference methods to guide strategic decision-making in revenue management.
Structured and analyzed experiments using DiD, RDD, synthetic controls, A/B testing, and Double Machine Learning to evaluate impact and inform policy.
Built scalable algorithms and tools for causal estimation, ensuring accuracy and seamless integration into production systems.
Collaborated with product managers, data engineers, and software developers to deliver end-to-end solutions powered by causal insights.
Stayed current with research in causal analysis while mentoring junior team members and fostering knowledge growth.
Requirements
5+ years of experience in Data Science with specialization in causal inference, particularly in pricing and marketing contexts, including work with sparse and volatile datasets.
Demonstrated expertise in designing and deploying causal frameworks to measure and validate the impact of revenue management and pricing strategies.
Strong foundation in statistical modeling and advanced causal inference methodologies.
Skilled in Double/Debiased Machine Learning (Double ML) for causal effect estimation using combined machine learning models.
Proficient in building and interpreting Causal Graphs and Structural Causal Models (DAGs) for robust causal identification.
Advanced application of Propensity Score Matching and Weighting to estimate treatment effects in observational studies.
Hands-on experience with Instrumental Variables (IV) and Synthetic Control Methods to assess causal impacts in complex environments.
Applied Difference-in-Differences (DiD) and Regression Discontinuity Design (RDD) to evaluate causal effects over time.
Fluent English. German is a plus
Benefits
28 vacation days
Hybrid model with flexible working hours
Partner discounts
Training programs, external conferences, and internal talks