About

Raghukul Raman is a highly motivated and skilled strategist at Quadeye Securities with a strong background in computer science. As a senior undergraduate at the Indian Institute of Technology - Kanpur, he is currently pursuing a bachelor's degree in computer science. With almost three years of relevant experience, Raghukul has a proven track record of success in the industry. He has previously worked as a Quantitative Research Intern at Tower Research, where he built machine learning and statistical models to predict market signals, which were used to generate buy-sell triggers for an aggressive trading strategy. He also experimented with neural models and ensembling to improve PnL scores. In addition, Raghukul has worked as a Software Tech. Intern at Dunzo, where he developed a horizontally scalable Geohash based storage architecture that impacted 1M orders/month. He implemented concurrent BFS over geo hashes for querying all runners and all queued tasks, using the Hungarian algorithm for task-runner matching. He leveraged his knowledge in concurrent software design to improve performance. Raghukul's technical expertise includes research scientist and machine learning. He has a deep understanding of statistical modeling, data analysis, and feature selection, and is proficient in Python, C++, and Java. Raghukul is a highly motivated and dedicated individual who is passionate about his work. He is always looking for new challenges and opportunities to learn and grow. With his exceptional skills and experience, he is a valuable asset to any team.