I am an experienced professional with prior experience building predictive models leveraging massive datasets using H2o, sklearn and other modeling libraries.Highly proficient in using Python, Hadoop map-reduce, PySpark SQL, RDD and DataFrame APIVery firm understanding of market-basket analysis, recommendation engines, streaming data and massive big data clustering algorithms like BFR, CURE. Hands on experience on AWS EC2, S3 and DynamoDB, MongoDB, Snowflake, DataBricksDelivered multiple projects in financial risk modeling to clients in UHG and managed end to end project pipeline.4 years of experience working in a fast paced team environment where I learnt to manage end to end project and client communication.I have a firm grip over Machine Learning algorithms like Linear Regression, Logistic regression , Random Forest, GBM, XGBoost, SVM, Neural Networks, Language modeling, markov chains, Naive Bayes and applied statistics, probability and computing algorithms required to successfully build a ML Project Pipeline.I have taken following Graduate Level courses at USC which have trained me to be a proficient ML Engineer-> Machine Learning for Data Science-> Foundations of Data Management -> Foundations and Applications of Data Mining-> Applied Natural Language Processing