Insight generation by building data mining and statistical models to support Customer Value Management (CVM) and Loyalty Programs by translating model outputs into actionable insights for business units

Data Mining & Advanced Analytics model development

• Actively use built-in data analytics models on CDP, including customer segmentation, churn prediction, propensity modelling and next-best activity; continuous update and adjustment of model parameters and performance tracking of the models on CDP
• Build advanced predictive analytics models offline by using programming languages such as R, Python, SQL and implement those models to CDP to generate them; score the model in other tools and integrate the results to CDP if the model is too complex to be generated on CDP; leveraging infrastructure including Cloud computing solutions and relational database environments
• Stay on top of changing conditions by retraining and testing the model regularly; enhance it whenever necessary
• Monitor models’ accuracy to catch any degradation in its performance over time
• Apply expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand user interactions

Insight generation

• Actively seek and identify where data science can provide value to business areas across the BUs, provide solutions to BUs analytical problems and validate the solution performance
• Generate actionable insights and predictive modeling techniques to modify consumer behavior

Reporting

• Active use of built-in reporting tools on CDP; day to day report generation and maintenance using BI tools and be involved in any new tool selection and deployment
• Engage with stakeholders to ensure that data insights are effectively communicated through the most appropriate data visualization and navigation tools