Manager (Lead Data Scientist) with close to 8 years of experience in Model Development and profound business knowledge in Banking Domain. Proficient in both traditional machine learning and advanced deep learning, GenAI techniques, with a proven track record of delivering optimized solutions to address complex business challenges. Demonstrated ability to work independently and collaboratively in cross-functional teams.Expert in Statistical Modeling, Hypothesis Testing, Loss Functions, Optimization Functions, Evaluation Metrics, Predictive Analytics, Data Wrangling, Data Exploration and Visualization, Data Mining, Feature Engineering, Hyperparameter Tuning, and Model Diagnosis.• Languages & Platforms: Python, SQL, Hive, R, Excel• Machine Learning Algorithms: Supervised learning, Linear & Logistic Regression, Decision Trees, Random Forest, XGBoost, LGBM, SVM, Naïve-Bayes, k-NN; Unsupervised learning, Clustering (k-means), Dimensionality Reduction, LLM, Deep Learning, GenAI, Network Graphs• Deep learning: ANN, CNN, RNN, LSTM, Transfomers, BERT, GPT• Statistical Methods: Probability & Statistics, Central Tendency, Central Limit Theorem, Standardization, Z-test, T-test, ANOVA, Chi-square Test, Covariance, Correlation• Frameworks & Libraries: pandas, numpy, scikit-learn, matplotlib, seaborn, nltk, statsmodels, tensorflow, keras, pytorch, opencv, flask, networkX