Oliver Cobb

Oliver Cobb

Applied Machine Learning Scientist @ Thomson Reuters

About Oliver Cobb

Oliver Cobb is an Applied Machine Learning Scientist at Thomson Reuters, where he has worked since 2023. He holds an MMath in Mathematics and Statistics from the University of Oxford and has previous experience in machine learning and statistical modeling.

Work at Thomson Reuters

Oliver Cobb has been employed at Thomson Reuters as an Applied Machine Learning Scientist since 2023. In this role, he applies his expertise in machine learning to develop innovative solutions and enhance data-driven decision-making processes within the organization. His work focuses on leveraging advanced algorithms and statistical methods to improve the efficiency and effectiveness of Thomson Reuters' offerings.

Education and Expertise

Oliver Cobb studied at the University of Oxford from 2015 to 2019, where he earned a Master of Mathematics (MMath) degree with a focus on Mathematics and Statistics. This educational background provided him with a strong foundation in quantitative analysis, statistical modeling, and mathematical theory, which he applies in his professional roles in machine learning and data science.

Background

Before joining Thomson Reuters, Oliver Cobb gained valuable experience in the field of machine learning and statistical modeling. He worked as a Statistical Modelling Intern at ATASS Sports for one month in 2018, where he contributed to sports analytics. He then served as a Machine Learning Research Scientist at CopernicAI from 2019 to 2020, followed by a position as an Applied Machine Learning Researcher at Seldon from 2020 to 2023.

Previous Roles in Machine Learning

Oliver Cobb has held several positions in the machine learning domain prior to his current role. He worked at CopernicAI as a Machine Learning Research Scientist for one year, where he focused on developing machine learning models. Following that, he spent three years at Seldon as an Applied Machine Learning Researcher, where he contributed to various projects aimed at deploying machine learning solutions in real-world applications.

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