About

Gourab Nath is an accomplished AI/ML/Data Science professional with over 26 years of relevant experience. Currently working as a Principal Data Scientist at Ericsson, Gourab has built low-MAPE regression models of radio access network KPI spikes and dips, shaping product design. He has also conceived and engineered a python package for collecting metadata over large segmented data files to pinpoint ill-formed data and evaluate data quality in general, with most features not yet addressed by Pandas Profiler. Gourab has participated in extended leadership activities of Ericsson GAIA, Ericsson's Global AI Accelerator division. Prior to Ericsson, Gourab worked as a Principal Data Scientist at Cumulus Networks, where he designed and implemented a generic Pyspark based package to seamlessly query S3 avro data over spark clusters, and studied how AI-enabled data centre management/network monitoring products are and should be, including defining AI/ML problems therein with the goal of incorporating such features into Cumulus's netQ product. He also worked on ARIMA based time-series trend prediction of Rx and Tx bytes of network switches, and anomaly detection for data quality over switch data. Gourab has also worked as a Senior Data Scientist/Architect at Unbxd Inc, where he designed, implemented, and deployed a prediction model for generating large scale customer affinities to user attributes for e-commerce personalization, with a repeat benefit data architecture for other data science problems. He mentored juniors and groomed Unbxd tech content for Berlin Buzzwords, Europe's premier dev conference. Gourab holds a degree in Entrepreneurship and Innovation from Stanford University. He has a strong tech stack that includes Data Scientist, AI, Research Scientist, ML, Spark, product designer, Python, Pandas, Software Engineer, Search, Supervised Learning, and Senior Software Engineer. Gourab is a highly skilled and experienced professional who is passionate about using AI and ML to solve real-world problems.