Shreekant Saurabh
About Shreekant Saurabh
Shreekant Saurabh is a Senior Data Scientist at MediaMarktSaturn in Munich, Germany, where he has worked since 2019. He has a background in Electronics and Communication Engineering and has experience in statistical modeling, artificial intelligence, and demand forecasting.
Work at MediaMarktSaturn
Shreekant Saurabh has been employed at MediaMarktSaturn as a Senior Data Scientist since 2019. In this role, he developed a web application utilizing R-shiny for Price Strategy Simulation. His work focuses on leveraging data science techniques to enhance pricing strategies and optimize business decisions within the organization. His contributions are significant in the Munich Area, Germany, where he applies his expertise in statistical modeling and data analysis.
Education and Expertise
Shreekant Saurabh earned his Engineer’s Degree in Electronics and Communication Engineering from PES Institute of Technology, studying from 2010 to 2014. Prior to this, he completed his high school education at D.A.V Public School in New Delhi from 2007 to 2009 and at Adwaita Mission High School from 1996 to 2006. His educational background provides a strong foundation in engineering principles, which he applies in his data science career.
Background
Before joining MediaMarktSaturn, Shreekant Saurabh worked at Vodafone as a Data Scientist from 2014 to 2016 in Bengaluru, India. He then transitioned to Hewlett-Packard, where he served as a Software Engineer specializing in Machine Learning and Deep Learning from 2016 to 2018. Following this, he held a position as a Senior Data Scientist at EY for four months in 2018. His diverse background in data science and software engineering has equipped him with a comprehensive skill set.
Achievements
Shreekant Saurabh has developed and improved statistical models to estimate Price Elasticity of Demand. He has implemented artificial intelligence automation for HP printers, utilizing technologies such as Computer Vision, Convolutional Neural Networks, Recurrent Neural Networks, and Natural Language Processing. Additionally, he has experience with Google Cloud Platform for data extraction, storage, and model deployment, and has conducted Seasonal Demand Forecasting using time series techniques including ARIMA, VAR, and Neural Networks.