With over a decade of experience in credit risk modeling across both Retail and Wholesale portfolios, Omveer specialize in regulatory models, including:Development of AIRB/IFRS9 models: PD, EAD, LGD, DoD, MoC, CyclicalityCECL/CCAR model development for PD, EAD, LGD/RecoveryPredictive models for loss and delinquency (loan/account level state transition using Monte Carlo simulation, survival models, segment level roll rate or vintage analysis)PiT PD stress testing models and Markov chain-based transition matricesApplication and behavior scorecard developmentOmveer possess extensive expertise in data science and machine learning, including attrition (churn) modeling, deep learning (ANN, CNN, RNN), exploratory data analysis (EDA), and statistical analysis on large datasets.My strong communication and leadership skills enable me to deliver complex analytical projects in collaboration with cross-functional teams.Skills:Cloud computing: GCP, AWSProgramming: Python (Numpy, Pandas, Scikit-Learn), SQL, SAS, R, BigQueryData preprocessing: SVD/PCA, TF-IDF, feature engineeringUnsupervised learning: Clustering (K-means, Dynoc)Supervised learning: Decision trees, random forests, regression, GBM, neural networksReinforcement learning: Q-learningMonte Carlo simulations, numerical methods