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Prateek Agarwal
Data Science at Walmart
About
Prateek Agarwal is an experienced Data Scientist currently working at Walmart. He is a skilled Deep Learning Engineer with expertise in Hadoop, Python, Deep Learning, and Computer Vision. With a Bachelor of Technology (B.Tech.) in Electrical Engineering from Delhi College of Engineering, Prateek has a strong engineering background. Prateek has a total of 5.79 years of relevant experience in the information technology and services industry. Prior to joining Walmart, he worked as a Data Scientist at Tiger Analytics, where he was involved in a shipment forecasting project for a global consumer goods-based company. He built flexible, scalable solutions in Python on the Google Cloud platform for data preprocessing, predictive modeling, and model explanation. Before Tiger Analytics, Prateek worked as a Project Engineer at Wipro, where he actively researched the latest advancements in the field of Object detection, Reinforcement learning, and Natural Language Processing. He worked on Facial Keypoints detection using IR camera in night driving conditions with a 3 pixel precision for a leading Asia Pacific customer. He also developed a Facial Recognition system for Wipod (Wipro’s autonomous vehicle) for authorization of a person to control the door. Additionally, he worked on a data pipeline on Microsoft Azure using Oracle as the data source for a leading Document solutions and services company. The pipeline aimed for data ingestion, transformation, and visualization in near-real-time. Prateek’s Tech Stack includes Data Science, Research Science, Deep Learning, Computer Vision, Python, SQL, NLP, OpenCV, ML, Hadoop, Reinforcement Learning, Object detection, CNN, Object Detection, and Azure. With his expertise in these areas, he has demonstrated his ability to deliver high-quality solutions to complex business problems.
Education Overview
• dtu delhi college of engineering
• father agnel school
Companies Overview
• walmart
• tiger analytics
• wipro
• indus action
Experience Overview
7.8 Years
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