Robust and accurate empirical evidence on the social world can empower organizations to make real-time effective decisions, develop successful products and gain a broad understanding of their markets. But accurate evidence require rigorous data collection, deep understanding of the biases that can emerge in observational data, and careful application of suitable statistical methods to analyze the data. To achieve this, I advice companies on how to collect, correct, measure and analyze their data. This includes:   
  • Assessment of accuracy and reliability of human labeling projects​
  • Bias assessment in ML models
  • Measurement design
  • Survey science and demography
  • Statistical analyses of observational data