About

Deepansh Goyal is an experienced member in the field of Deep Learning with a strong background in Python, C++, and Pytorch (AI). He is currently working as a Big Data Developer at Societe Generale where he is responsible for creating Cloud Data Lakes on Azure and pipelines to ingest data across these systems. He is also instrumental in instrumenting pipelines to facilitate migration of data to Cloud Data Lake from On-Premise clusters, creating new services on Kubernetes as pods, and extracting data pipelines for downstreams using BigData principles to reduce the dependency on On-premise systems. Deepansh has a Bachelor of Technology degree focused in Metallurgical Engineering from the Indian Institute of Technology, Roorkee. He has worked as a Research and Development Specialist at Parimal Lab, IIT Roorkee, where he worked on a Segmentation Problem, a classical Deep learning Problem. He also secured the 5th position among 100 teams participating in the IDD-Lite Challenge organized by IIIT Hyderabad. In addition to his work experience, Deepansh has also served as the Secretary of the Photography Section at IIT Roorkee. He was responsible for managing 400+ students enrolled in the photography section, organizing multiple workshops from the basics of photography to advanced courses, and managing the total budget of INR 1.5 lakhs for the betterment of the Section. Deepansh's technical expertise includes Big Data, Spark, Azure, SQL, Hadoop, Kubernetes, Python, AI, Deep Learning, MapReduce, CI/CD, Data Scientist, Postgres, Pytorch, UI, Java, Spring, Neural Networks, Jenkins, and Apache Hive. He has 1.86 years of relevant experience in the industry and has deployed many deliveries to the production environment both Spark processes on HDInsight Cluster and Kubernetes pods. He has also assisted the team on many production issues and root cause analysis for the same issues and provided on-call rotations/support.