CHANDAN MONDAL

Checking & Savings New Production Model is developed to predict number of newly opened Checking & Savings account leveraging statistical analysis based on Consumer, Business & account Balance Tiers’ Segment. This model is also used to forecast Average account balance with Time Series Forecasting Analysis. Checking & Savings Tenured model is developed to serve three major purposes leveraging statistical modelling, time series analysis and macroeconomic factors. Purpose is to predict firm-wide checking & savings attrition rate, average balance amount per account & balance tier transition. Model Management & Monitoring: Responsible for model management in the area of Finance and Marketing along with their deployment on-prem and cloud. Defining the strategies and framework for the initial setups of the new model and their long run requirements on regulations.

Named Entity Recognition model which is applied to automatically tag and extract entities within chat messages from clients and brokers by the Sales & Trading team on an ad-hoc basis. The model was developed using bi-LSTM deep learning methodology. HR Manager Evaluation Quality Check Model was developed to automate the process of identifying manager’s year-end reviews content into sufficient and deficient using Random Forest& GBM Machine Learning techniques. Sales Practices Complaints Risk Identification Model to classify the SP related complaints leveraging Natural Language Processing and extreme Gradient Boosting Model in the H2O.ai driverless AutoML platform. Systran Model to translate features for documents master center information from source language to target language. Machine Learning Research Project was developed to understand interpretability and explainability of NLP based machine learning models with LIME and Shapley methodology. Also, different hyperparameter optimization techniques were studied to get optimal modelling results as per business application of the ML model.

Knowledgeable Data Scientist well-versed in due diligence, valuations and statistical analysis. Prepares machine learning, deep learning, statistical models, forecasts trends and communicating outcomes to the Stakeholders. Detailed in data analysis and reporting for audits, trend determination and financial planning. Profoundly knowledgeable into Banking & Finance Domain in applied statistical and AI ML model review and validation.