AI ML Data Scientist

AI ML Data ScientistMust Have Technical/Functional SkillsMachine Learning techniquesUnsupervised - K-means Clustering, PCA - Dimension Reduction, Kernel Density Estimations.Supervised - Regression, Decision Trees, Random forest, XG Boost algorithm,Time series - Exponential models, Holt-Winters, ETS, Hybrid, ARIMA & GARCH.Deep LearningNeural Network, Recurrent Neural Networks,DatabaseSQL, Advance SQL, Oracle, NoSQLData Science LanguagesSAS, SAS Enterprise Miner, R Programming,Python, Spark.Statistical & Data Management PackagesPython - Pandas, Numpy, sklearn, PyOdbcR- dplyr, car, caret, lubridate, zoo, Rminer, R-OdbcVisualizationTableau, Shiny, ggplot2, dygraphs, matplotlib, seaborn.Big Data TechnologiesSpark (Pyspark & SparkR), Hadoop, Yarn.PM ToolsMS Project, MS Visio, TFS, JIRACloud, Web frameworks & VirtualizationAzure, Flask, Docker & Kubernets, KafkaRoles & ResponsibilitiesData Scientist with 5-10+ years of result-oriented, hands-on professional experience with a successful record of accomplishments in Data Science & Analytics and Project management in Banking and Financial Services.Expertise in Predictive Modeling and Big Data Analytics, Statistical model development, Implementations & Optimization techniques.Proficiency in implementing Machine learning techniques -Regression, Decision Tree Learning, Neural networks, Random Forest and XGBoost-in various business problems (AML, fraud detection, mortgage default, foreclosure, credit risk management, price prediction and optimization).Strong leadership and capacity to work as a team player, as well as excellent communication skills.Some knowledge on various aspects of Retail and Wholesale Consumer banking and US Mortgage Banking.