About

Kumar Raj is a highly skilled and experienced Software Engineer and Data Scientist with over 7 years of expertise in applying machine learning and performing deep analytics in the cloud infrastructure domain. He has a Bachelor of Technology degree from one of the topmost engineering institutes in India, the Indian Institute of Technology, Kharagpur (IIT KGP), with an acceptance rate of only 0.7% at the bachelor's level. Kumar has a granted patent (US Patent No.10,789,146) in "Time series forecasting of data center workloads" applied by Hewlett Packard Enterprise. He is also a co-author of the paper presented in USENIX, HotStorage'16, on "Accelerating analytics workflow in low latency storage systems." Kumar is passionate about coding and has extensive knowledge of Software designs, Statistics, Predictive Analytics, and Text Analytics using Python and R. He is well-versed in SQL and MapReduce for querying relational and NoSQL databases. Kumar has a good understanding of algorithms and data structures. He possesses excellent skills in Python, R programming, and Tableau, and has a sound knowledge of various machine learning algorithms for classification and regression problems. He is proficient with querying in Microsoft SQL Server and MapReduce querying in MongoDB. Kumar has an understanding of NoSQL databases like MongoDB and GraphDB (NEO4J). Currently, Kumar works as a Staff Software Developer (Data Science) at Qualcomm, where he optimizes the compute environment efficiency for Qualcomm's mega data centers. He has developed a memory and CPU prediction engine to accurately predict compute resource requirements by EDA jobs to avoid wastages and improve cluster utilization. Kumar has also developed a dynamic compute capacity allocation algorithm that ensures the right machine mix allocation in clusters for every functional group based on historical data. In his previous roles, Kumar worked as a Data Scientist II at Hewlett Packard, where he developed a resource utilization forecasting algorithm for HPE's Server virtualization software "Cloud Optimizer." He also worked with ML-based startups in HR analytics and customer service analytics, where he built an employee joining failure propensity model for an international HR consultancy company and developed a Text parser for parsing PDF documents and word documents. Kumar's education history includes a Nanodegree in Machine Learning Engineering from Udacity and a Bachelor of Technology (B.Tech.) in Agricultural and Food Engineering from IIT Kharagpur. He has a strong tech stack that includes Software Engineering, Data Science, SQL,