Vijay Gaikwad has a strong background in machine learning and data science. Vijay is currently serving as the Director of Data Science & Machine Learning at Found since February 2023. Prior to that, they worked at Loftium, where they held the positions of Head of Machine Learning and Senior Machine Learning Engineer. During their time at Loftium, they played a critical role in leading machine learning, data science, and analytics initiatives. Vijay was responsible for driving complex decision-making processes, such as property acquisition, revenue optimization, and financial forecasting for growth and expansion.
Before joining Loftium, Vijay worked at 98point6 Inc. as a Senior Machine Learning Engineer. Vijay focused on natural language understanding of medical text in the company's chat-based primary healthcare app. Vijay'swork included projects like AI chatbot, AI-based medical diagnosis, and prescription inference. Vijay was involved in building data pipelines, experimenting with deep learning models, and developing machine learning services for product integration.
Earlier in their career, Vijay worked at Microsoft as a Software Engineer. Vijay was part of the Azure Cloud Compute team, where they contributed to building a big data analytics platform and supply chain automation. Vijay was responsible for developing web services using .NET technology on the Azure Cloud stack. Vijay'swork supported Azure's data center infrastructure and monitoring and analytics platform.
Overall, Vijay Gaikwad's work experience showcases their expertise in machine learning, data science, and software engineering in various industries and domains.
Vijay Gaikwad earned a Bachelor's Degree in Computer Engineering from the University of Mumbai, from 2008 to 2012. Subsequently, they pursued a Master's Degree in Information Management - Data Science from the University of Washington, from 2012 to 2014. In addition to their formal education, Vijay also obtained a certification in Deep Learning from Coursera Course Certificates in October 2017.
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