Dipanjan Deb is an experienced analytics professional with about 16 years of cumulative experience in machine/statistical learning, data mining, and predictive analytics across the healthcare, maritime, automotive, energy, CPG, and human resource domains. He is highly proficient in developing cutting-edge analytic solutions using open source and commercial packages to integrate multiple systems to provide massively parallelized and large-scale optimization.

He has extensive experience in building analytics teams of data scientists that deliver high-quality solutions. Dipanjan strategizes and collaborates with industry experts, technical experts, and data scientists to build analytic solutions that shorten the transition from a POC to commercial release.

He is well versed in overarching supervised, semi-supervised, and unsupervised learning algorithm implementations in R, Python, Vowpal Wabbit, Julia, and SAS; and distributed frameworks, including Hadoop and Spark, both in-premise and in cloud environments. He is a part-time Kaggler and IoT/IIoT enthusiast (Raspberry Pi and Arduino prototyping).