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
• $100,000
• 120,000 a year #LI-OJ1