Samarth Singh is a Senior Quantitative Researcher at WorldQuant since July 2022, focusing on developing systematic tradable strategies utilizing an existing pool of alphas across various regions. Prior experience includes a role as a Quantitative Researcher, where algorithm development and back-testing for global equity instruments were primary responsibilities. Samarth previously interned at Adobe in 2021, optimizing metric data processes and developing an API layer for an NFT trading platform, leading to a full-time offer for an MTS role. As a Teaching Assistant at the Indian Institute of Technology, Bombay, responsibilities included assisting in courses on programming under multiple professors. Samarth holds a Bachelor of Technology degree in Computer Science and Engineering from the Indian Institute of Technology, Bombay, completed in 2022.
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