Innovative Data Scientist with 6 years of experience in analytics and success in credit risk management, digitization and customer relationship management. Highly accomplished in influencing decision-makers and driving profitability across multiple divisions, including banking credit risk, debt collections, customer relationship management and digitization. Eager to bring expertise to growing organization in challenging new role.
● Helped to analyze buyer and seller fraud.
● Working in NA,APAC,EMEA,AU market.
● Closely working with the real time money flow.
● Working in buyer chargeback.
● Helped newly registered customer account validation.
● Working closely with CRI(Consumer Risk Investigation) team.
● Investigate customer account for the risk issues.
● Used analytical tool like Tableau and data visualization tool Power BI.
● Handling the issues of Unauthorized card use/bank acc use, fraud account creation, money laundering etc
● Handling backend operation in Financial Technical (FINTECH) Domain.
● Worked in consumer Finance.
Project (Buy Now Pay Later) :
● Worked in ‘Buy now pay later’ pilot team and launched the product for Indian customers.
● Created template on financial sms of customers and verified that templates which helps to filter the customers for ‘buy now pay later’
● Used Apache Spark for clustering the Big data(mostly financial/promotional sms) of flipkart customers
● Used analytical tool like MySQL
Programing Language: Python ; R
Personal Projects
Yourcabs.com:
Built a model to tackle the business problem and tried to improve customer service for YourCabs.com a cab company in Bangalore, a cab company in Bangalore.
Problem statement: The problem of interest is booking cancellations by the company due to the unavailability of a car. The challenge is that cancellations can occur very close to the trip start time, thereby causing passengers inconvenience.
Built a model using Random Forest.
Customer retention modelling:
This analysis focuses on the behavior of telecom customers who are more likely to leave the platform. I intend to find out the most striking behavior of customers through EDA and later on use some of the predictive analytics techniques to determine the customers who are most likely to churn. Performed EDA by using pandas, matplotlib, and seaborn. Converted the categorical features into numerical values. Remove Features with O Variance. Conducted univariate and bivariate data analysis.
Built Logistic Regression model
Entry Certificate in Business Analysis (ECBA)
Cricket is my passion. Love to play cricket.
Love to explore new places and interact with different people
Cricket is my passion. Love to play cricket.
Love to explore new places and interact with different people