Kuldeep Singh

• Worked with capital market team to analyse data and provide actionable business intelligence to stack holders • Producing a dashboard using daily data feeds • In order to create and support the underlying assumptions and inputs for current models, big data sets were processed, correlations, univariate, bivariate, missing value reports were developed, Automation of reports using python and excel • Used statistical analysis to examine significant data sets pertaining to crucial business processes

• Created, optimized and applied machine learning models • Having experience with Python scraping using selenium and beautiful soup, scrapy to scrape dynamic webpages, HTML, PDF, CSV,.XML, and JSON files • Experience in developing data pipeline (ETL pipeline) using azure data bricks, azure blob storage and azure devops and github for version control • Perform Basic and advance level transformations by applying business rules

• Experience in developing statistical analysis reports that involve data collecting, data cleansing, univariate and bivariate analysis, as well as data visualization • Developing risk segmentation scorecards for unsured business with algorithms like logistic regression, linear regression, and decision trees aids in predicting the quality and obligation of a customer's loan application and reduces delinquent • Credit risk analytics for bank's retail assets -Personal Loan, Business Loan and Credit Cards

• Performed data mining, data cleaning, explored data visualization, building machine learning and statistical model techniques using R, MYSQL and other analytical tools. • Extensively used Joins and sub-Queries to simplify complex queries involving multiple tables. • Developed ad-hoc queries using MYSQL and R language. • Design of experiments [ Adjusted /varied interest rate] – initiated design of experiment to dynamically adjusted interest rate based on customer profile and credit behavior.

• Performed data mining, data cleaning, explored data visualization, building machine learning and statistical model techniques using R, MySQL and other analytical tools • Extensively used Joins and sub-Queries to simplify complex queries involving multiple tables • Developed ad-hoc queries using MySQL and R language. Performed data extraction and manipulation over large relational data sets using R and SQL

1 - Business Communication 2 - Global Business Environment 3 - Management Control System 4 - MIS for Global Organization

1 - Computer Based Numerical and Statistical Technic. 2 - Data Structure using C 3 - Design and Analysis of algorithms 4 - Computer Graphics 5 - Computer Design 6 - Discrete Structure 7 - Digital Image Processing 8 - Introduction of web Technology