MSc in a quantitative field, preferably statistics.
Hands-on experience (typically approx. 4- 6 years) carrying out data analytics, data mining and product analytics in sophisticated, fast-paced environments.
Applied knowledge of data analytics and data pipelining tools and approaches across all data lifecycle stages.
Deep understanding of a few and a high-level understanding of several commonly available statistics approaches
Advanced SQL knowledge
Advanced scripting experience in R or Python.
Ability to write and maintain moderately complex data pipelines.
Strong business insight.
Customer-centric and pragmatic approach. Focus on value delivery and swift execution, while maintaining attention to detail.
Good communication and customer leadership skills. Ability to lead large organizations through influence!