About

Ambrish Kumar Soni is a highly experienced data-centric machine learning enabler with expertise in edge analytics, video, and operations. With over 10 years of experience in predictive modeling, machine learning, and data engineering, he has a deep understanding of data science and artificial intelligence pipelines. Ambrish is skilled in conceptualizing, designing frameworks, and executing data science pipelines, including building, training, tuning, deploying, and monitoring. He has worked extensively with Python, R, and Java, and enjoys discussing the bigger picture and business impact as much as diving into details about all sorts of machine learning and statistical models. Currently working as a Machine Learning Architect at Pitney Bowes, Ambrish is involved in a project that uses machine learning and data science capabilities to optimize various global cross-border eCommerce solutions. He is responsible for designing and defining the data science architecture for products, developing predictive algorithms to solve complex business challenges, and extracting information from data sets. Ambrish has delivered end-to-end machine learning products, including data collecting, exploratory analysis, feature engineering, and choosing the right algorithm to train the models. He has also designed text classification and NLP architecture, approach building for unstructured data, and worked on data preparation and exploration using Python, R, and SQL. In addition to his current role, Ambrish has previously worked as a Senior Software Engineer at Pitney Bowes and a Software Engineer at eBay. He holds a Bachelor’s degree in Computer Science and Engineering from UPTU. Ambrish’s tech stack includes ML, senior software engineering, data science, SQL, text classification, random forest, Python, NLP, software engineering, data engineering, and Java. With 13.02 years of relevant experience, Ambrish is a highly skilled and knowledgeable data-centric machine learning enabler.