Job Description
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.