• TO FORECAST WHETHER A CUSTOMER WILL TURN OUT TO BUY A TERM DEPOSIT AFTER HAVING CONVERSATION WITH BANK SALES TEAM
• Estimating whether customer will turn out to be fraud
• Based on historical data, EMI, Income, Asset Value, Demographic information etc., are used in analysis to estimate the fraudulent nature of customer.
• Done univariate and multivariate exploratory data analysis
• Data pre-processing and merging based on unique ID of customers to extract features
• Merging different files based on customer ID to bring them under same data structure
• Develop complex models and algorithms that drive innovation and performance throughout the organization. This may include improving on-time performance, network planning, etc.
• Develop processes and tools to monitor and analyse model performance and data accuracy
• Conduct advanced analytics to provide actionable insights, identify trends, and measure performance.

Automation project

• Used python to update the content in the datasets and manipulate the files
• Installed python libraries using pip command
• Assemble large, complex datasets that meet functional / non-functional business requirements
• Added several options to the application to choose a particular algorithm for data and address generation
• Managed large data sets using pandas data frames
• Implement and review coding standards
• Resolving bugs