AI ML Data Scientist

Role: AI ML Data Scientist

Location: Cary, North Carolina, United States

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.