Experienced in machine learning classification and clustering projects. Created a reconciliation break prediction system for mutual funds using decision tree classification. This system improved the break resolution efficiency by 25%. Created an automatic defect categorization system to classify similar defects into categories using k-Mean clustering. This clusters helped application owners to identify the processes which are causing issues and allow them to do preventive maintenance in their applications. This reduced the frequency of repeated incidents and making the application stable.