UTTAM KUMAR GUPTA

[email protected] • (+91) 9907920994
LinkedIn: LinkedIn - Uttam Kumar Gupta • GitHub: github.com/ukg9

PROFESSIONAL SUMMARY

I am a detail-oriented Business Analyst with 3+ years of experience, specializing in credit risk, model validation, and regulatory frameworks such as IFRS 9 and CECL within the banking and financial services sector. I have strong experience in interpreting and analyzing complex datasets to support credit risk assessment, expected credit loss (ECL) modeling, and regulatory compliance. I possess proficient knowledge of statistics, mathematics, and advanced analytics, along with a solid understanding of business operations and analytical tools (SAS) to deliver effective, data-driven business solutions.

WORK EXPERIENCE

TEAM DEVELOPER
02/2024 - 05/2025
Anaptyss Ind. Pvt. Ltd.
• My role focuses on validating Credit Risk models to ensure compliance with Basel II regulatory standards, and internal risk governance frameworks. I support risk management efforts by assessing model performance, conducting thorough documentation reviews, and preparing accurate validation reports for audit and regulatory checks.
• Validate scoring models used by client and prepare Model Documentation Reports (MDR) on their performance using the key performance indicators (KPIs) of different vendor (bureau) models.
• Created coded programs using python, replicating results and independent testing. Conduct performance monitoring of the pre developed models based on ML techniques like logistic regression using various monitoring metrics like R-square, PSI, etc. and prepare performance review reports.
BUSINESS ANALYST
09/2020 - 03/2023
EXL Services
• Assessing quality of model outputs through back-testing against realized outcomes, benchmarking against alternative models and regulatory expectations, verifying model accuracy, implementation, and reconciling large data inputs
• Created coded programs using SAS to replicate results and perform independent testing, quarterly and annual validation of pre-developed models based on logistic and linear regression using monitoring metrics such as R-square, PSI, etc., and preparation of MIS and Annual Model Review (AMR) reports

EDUCATION

MBA in FINANCE
01/2017 - 01/2019
Monad University, Delhi NCR
B.Tech in Aeronautical Engineering
01/2013 - 01/2017
Swami Vivekananda University. M.P.

SKILLS

Technical Skills: Predictive Modeling, Model Validation, Exploratory Data Analysis, Model Monitoring, Logistic Regression, Key Performance Metrics, Root Cause Analysis, Python, SAS Base, SAS SQL, SAS Macros
Soft Skills: Adaptability, Problem Solving, Analytical Thinking, Attention to Detail
Tools: SAS, Python IDE, MIS Reporting Tools
Other: Data Analytics, Statistical Modeling, Team Collaboration, Industry Knowledge: Analytics

PROJECTS

Propensity model (logistic regression – response prediction)
Technologies: SAS, Logistic Regression, Exploratory Data Analysis
• Built and deployed a logistic regression-based propensity model to predict customer response (good vs bad) to a bank-offered insurance product
• Executed comprehensive data preprocessing followed by exploratory data analysis (EDA) to gain insights into the data to guide model building
• Modeled in SAS, predicting the likelihood of positive customer engagement with the product and evaluated the performance using AUC, Gini coefficient, and KS statistic to ensure robust discrimination between goods and bads
• Conducted model validation using holdout data, ensuring minimal drift and high generalization capability for production use
• Impact: Enabled marketing team to target high-propensity customers more effectively, resulting in a 20% improvement in campaign response rate and reduced acquisition cost through focused outreach

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