About

Bhuvanesh Srivastava is a highly skilled engineering professional with over 7 years of experience in the field of Data Science and Data Engineering. He holds a Master's Degree in Machine Learning, Big Data, Data Modeling, and Statistics from IIIT Bangalore. Bhuvanesh has worked in various domains such as Finance Risk (CCAR), Finance, Marketing, and Sales, and has experience in all layers of the full data stack. Currently working as a Software Engineer 2 at Uber, Bhuvanesh is part of the FinTech Insights & Data Engineering Team. He has independently handled billions of data points daily, including ingesting, transforming, data modeling, creating ERDs, generating insights, and visualizing data using Tableau. Bhuvanesh has also created a utility using Tableau API, which allows Tableau extracts to refresh as soon as the latest data is available in base tables, saving about 4 hours on SLA. He has also created a Conversational AI Chatbot for the team, which educates end-users on their team and data, and creates Hive/Presto queries on the fly for non-technical end-users. Bhuvanesh has previously worked as a Senior Software Engineer (Big Data Analytics) at LogMeIn, where he was responsible for designing ETL pipelines in PySpark and modeling data warehouse Hive tables to handle millions of data records daily in a scalable fashion for various company products. He has also built analytics on top of the data, such as customer churn prediction, products upsell & cross-sell for the sales team, and creating Tableau reports that show customers 360 views, which is used daily by about 300 end-users. Bhuvanesh has also spent time on data governance efforts, ensuring the quality of data in their centralized data warehouse is top-notch. Bhuvanesh's technical skills include AWS, AI, ETL, ML, Python, Big Data, Data Engineering, Apache Hive, SQL, NLP, Data Scientist, Research Scientist, Hadoop, Apache Airflow, and Tableau. He is a highly motivated individual with a passion for solving complex data problems and delivering business value through data-driven insights.