Certified Data Scientist with 11 years of IT experience in Finance domain. Highly skilled in machine learning, data visualization, and natural language processing.

• Created a reconciliation break prediction system for mutual funds using decision tree classification. This system improved the break resolution efficiency by 25%.
• Created a recommendation system for suggesting the best solution for production incidents. This reduced the manual effort required in finding a solution and thereby reducing the turnaround time for fixing an incident.
• 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.
• Created a Chabot to guide traders on their day to day activities on the trade floor using natural language processing. This helped the trade floor teams to reduce the time required to get their queries answered and become more productive.