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

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