About

Umesh is a highly skilled Data Engineer and Machine Learning Enthusiast with over 6 years of experience in ETL pipeline for big data projects and Data Analysis. He has experience with all stages of the development cycle for complex data loads and predictive analysis projects. He has taken several Data Science focused courses at Applied AI course, including Python programming, Machine Learning, Linear Algebra, Probability and Statistics, and Natural Language Processing. Umesh is a technology-savvy and mathematically-equipped professional who gets a good kick out of analyzing data. He has good hands-on experience in processing Big data using distributed frameworks such as Spark, Scala, and Python, data warehouse tools like Snowflake, distributed databases like Cassandra and Hbase, and distributed file systems like HDFS and Auxillo. He has extensive knowledge of Machine Learning algorithms, including Unsupervised algorithms like K-means clustering, Hierarchical clustering, and DBSCAN, Dimensionality reduction and visualization tools like PCA and t-sne, Supervised algorithms like Naive Bayes, Logistic Regression, Linear Regression, SVM, and Tree-based algorithms like Decision Trees, Random Forest, Adaboost, and Grandient Boosting Machine. He is also proficient in Deep Learning algorithms like Multi-layer perception (MLP), Convolution neural network (CNN), Recurrent neural network (RNN), and Time Series Analysis. Umesh has a strong background in statistics, including exploratory data analysis using statistical tools, probability theory, and distribution function. He is proficient in programming languages such as Python, Scala, Shell scripting, and SQL. He has extensive knowledge of Big data frameworks like Spark, Snowflake, Hadoop, Databricks, NumPy, SciPy, Pandas, Matplotlib, NLTK, TensorFlow, and Keras. He is experienced in Big data filesystems like HDFS and Azure Blob, databases like Postgres, Snowsql, HBase, Hive, and Cassandra, and schedulers like Airflow. He is also proficient in cloud platforms like Azure. Currently, Umesh is working as a Data Engineer at Accion Labs, where he has designed and implemented a generic Azure Data Pipeline and Spark based Model for batch processing of enterprise-level complex retail data, resulting in saving $5000 per month. He has also developed and maintained a reporting tool to ensure 100% errors were recorded and reported. Umesh has previously worked at Reni Analytics and Mindtree, where he has implemented various predictive analysis projects and automated distributed