Bio

10+ Years of experience in Machine Learning and Decision Science T1 global talent UK Visa holder Experienced in credit risk modelling, transaction data-based risk scorecard, liquidity modelling, next best action modelling, customer churn modelling, insurance modelling, financial crime models, graph-based crime modelling, financial distress modelling, business customer risk models Expert in Fair and Ethical AI implementation Fluent with Python and R, have experience with Spark, worked on AWS, Azure and GCP Mentored starts-up and student on AI and ML Conversant with predictive modelling, forecasting, text analysis, network analysis, sentiment analysis, neural networks, Marketing analytics, conjoint analysis, market basket analysis, multivariate regression, OLS, Marketing Mix Modelling, factor and component analysis Excellent understanding of regression, logistic regression, multinomial regression, Poisson regression, panel data logistic regression, imputation, offset regression, negative binomial regression, Generalized Linear Model / Generalized Linear Mixed Model (GLM/GLMM), Survival Analysis, ARMA / ARIMA, ARCH / GARCH forecasting, time-series forecasting, simulation, association rules, segmentation, big data management, clustering, feature extraction, classification, Market engineering / Mixed Modelling Deep understanding of advanced Machine learning algorithms Certified in Predictive Modelling in SAS E-Miner from SAS institute Developed content for Edureka, Grey Campus and Edupristine on Business Analytics, Advanced Predictive Modelling, Data Visualization, Machine Learning Speaker for multiple conferences on topics realted to AI