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Ruben Nakano

Graduate StudentEmail Ruben Nakano

Ruben earned his Bachelor's degree in Civil Engineering from the Universidade de São Paulo in 2016. Throughout his undergraduate journey, he developed a keen interest in Operations Research and Optimization. What intrigued him most was the potential of using both statistical methods and heuristics to influence a wide spectrum of areas, ranging from corporate strategy to optimizing urban transit systems. After graduating, Ruben joined a consulting firm specialized in Logistics and Transportation and immersed himself in a role that demanded not only rigorous quantitative skills but also a mastery of soft skills. His projects were diverse: from optimizing transportation routes for sugarcane mills, to forecasting Brazilian soybean exports and training regression models for estimating air travel demand in airports. Beyond the technical aspects, he learned how to manage multiple clients and stakeholders, ensuring that all parties were aligned and informed. His ability to communicate intricate data findings in a digestible manner, coupled with his knack for fostering meaningful relationships, proved invaluable. In early 2020, just before the COVID pandemic struck Brazil, Ruben joined iFood, Latin America's premier food delivery company. During this tumultuous period, he played a pivotal role in ensuring the company's logistics ran smoothly. He supervised the rollout of machine learning models to predict Estimated Time of Arrival, introduced protocols to enhance order batching, and refined supply and demand forecasting models. This role marked his inaugural experience managing a team, offering a valuable opportunity to further refine both his technical expertise and interpersonal skills. Since coming to the MLDS program, Ruben has further honed his technical expertise, immersing himself in a spectrum of advanced subjects ranging from deep learning to big data computing, cloud engineering, network analysis, and natural language processing. This comprehensive exposure has equipped him with a multifaceted understanding of the current landscape of data science and its myriad applications. This past summer, he transitioned his knowledge from the classroom to real-world application during his internship at Uber. As a member of a marketing data science team, he engaged in hypothesis testing and causal inference for CRM campaigns and delved into analyzing product cannibalization. This experience allowed him to not only implement what he had learned but also to contribute actively to innovative projects. With the rich knowledge and skills he's amassed, Ruben is enthusiastic about the future, aiming to address pertinent challenges using data-driven insights and solutions.