Advanced Statistics and Data Mining
Application of Statistical Inference techniques, Factor Analysis and Cluster Analysis (interdependence techniques) for market segmentation purposes and analysis of underlying constructs of customer behaviour data. Discrete choice models for cross-sectional and panel data with limited dependent variable, Data Mining and Knowledge Discovery in Databases using conventional Methods (Decision Trees etc.) and Computational Intelligence (Artificial Neural Networks, Support Vector Machines etc.), application of SAS Enterprise Miner, SPSS Clementine & specialised software for Data Mining, domain expertise in temporal data mining & customer relationship management and Business Intelligence through enhanced decision making.
