Using CRISP-DM framework to implement data models and roll them to production- Supporting Data Science zone within Data Lake- Developing various machine learning use cases- Creating data models- Visualization of the results- Implementing ML for a procurement system

Performing data analysis and initial visualization of the retrospective spending- Building up several trends (pessimistic, realistic, optimistic) with current approach- Developing the model which would consider the change of the program rules- Presenting result of the modeling to the board member

- Evaluate the user LTV, ARPPU, Churn probability and other metric- Conducting analysis and visualisation of the result in Tableau- Calculate ROI of the user- Build tool to prioritize user’s support tickets