AI ML Data Scientist

AI ML Data Scientist
Must Have Technical/Functional Skills -Machine Learning techniques • Unsupervised - 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 Learning • Neural Network, Recurrent Neural Networks, -Database • SQL, Advance SQL, Oracle, NoSQL -Data Science Languages • SAS, SAS Enterprise Miner, R Programming, • Python, Spark. Statistical & Data Management Packages • Python - Pandas, Numpy, sklearn, PyOdbc • R- dplyr, car, caret, lubridate, zoo, Rminer, R-Odbc -Visualization • Tableau, Shiny,ggplot2, dygraphs, matplotlib, seaborn. -Big Data Technologies • Spark (Pyspark & SparkR),Hadoop,Yarn. -PM Tools • MS Project, MS Visio, TFS, JIRA -Cloud ,Web frameworks & Virtualization • Azure, Flask, Docker & Kubernets, Kafka
Roles & Responsibilities • -Data 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.
Salary Range- $90,000-$100,000 a year #LI-OJ1