• Develop, test and productionize attribution and predictive algorithms by using state of the art machine learning algorithms and optimisation models
• Contribute to one or more of the following areas: attribution modeling, CAC/mCAC modeling, LTV prediction, marketing mix modeling and multichannel attribution and testing
• Design experiments and interpret the results to draw detailed and actionable conclusions
• Work in cross-functional teams across disciplines such as product, engineering and business.
• Develop, test and own our production marketing attribution models for better budgeting and increased marketing efficiency

YOU HAVE

• 5 years of professional experience outside of an academic and internship setting, in a quantitative analysis role in top companies. FMCG or Fintech preferred.
• Holds at least an MSc, and preferably a PhD in a scientific discipline such as Physics, Statistics, Engineering, Computer Science or Mathematics
• Deep theoretical and applied knowledge in the following areas: statistical inference, bayesian statistics, causal inference, time series analysis and mathematical optimisation.
• Extensive experience at least in Multichannel Attribution Modeling and Marketing Mix Modeling
• Extensive experience in statistical programming (Python) and experience working with popular tools such as Pandas, SciPy, XGBoost, Jupyter/iPython notebooks and well-known modeling packages such as PyMC3
• Extensive experience with the end-to-end predictive/prescriptive model development cycle, from problem definition to productionalization and maintenance. This includes excellent data modeling and SQL skills, and familiarity with Cloud infrastructure.
• Demonstrated experience in designing and analyzing experiments in digital products (A/B test, multivariate, etc.)
• Experience with the application of statistical modeling and advanced analytics to provide product-shaping insights
• Excellent spoken and written English