Pinto Bhusan Datta

• Conducted a comprehensive review of R code for critical functions—such as Ex-ante Risk Limits, Risk Reporting, and Credit Portfolio Risk Modeling (J.P. Morgan’s CreditMetrics). • Implemented additional statistical validation tests and model parameter optimization for the portfolio model. • Monitoring and enhancing counterparty ratings using the CreditLens (Moody’s Analytics) platform and providing comprehensive support for data model maintenance, ensuring the Reliability and Efficiency of backend R Code.

Validated LGD and EaD models through quantitative and qualitative tests per ECB guidelines. Developed SAS code for stochastic differential equations and introduced time series regression benchmarks for funding and liquidity model validation. Enhanced efficiency by transitioning data analysis and validation tests entirely to SAS. Conducted workshops: 1. Simple Linear Regression with Panel Data and 2. Advanced Statistical Hypothesis Testing under ECB standards.

Analyzed data to produce risk-related reports and automated other reports and process using R and SQL, reducing manual work by over 70% and improving accuracy and data governance. • Collaborated on cross-functional IT projects to develop predictive models and automate processes, boosting efficiency by over 80% and cutting manual tasks by over 60%.

Courses: Master Thesis: Predictive Model Evaluation: Loan Default Time Prediction with Weibull Time to Failure-RNN Survival Analysis, Scientific Project: Mixed Multinomial Logistic Regression, Seminar: Assortment Optimization under the Mixed Multinomial Logistic Model, Machine Learning, Data Mining, Database Concepts, Predictive Analytics and Forecasting, AI-based Decision Support, Approximate Dynamic Programming, Business Forecasting, Marketing Methods and Analysis , Econometrics

Courses Multivariate Analysis Time Series Analysis Statistical Inference-II Sampling Techniques Biostatistics-II Advanced Demography Research Methodology Thesis

Courses: Algebra Calculus Linear Algebra Advanced Calculus & Differential Equations Real Analysis Numerical Methods & Complex Variable Statistical Programming-I & IIand Lab Multivariate Analysis Principles of Economics (Micro & Macro) Econometrics Economic Statistics Stochastic Processes Linear Programming Probability Principles of Statistics Theory of Statistics Applied Statistics Statistical Inference Survey Methods Regression Analysis Design and Analysis of Experiment I & II