Ilias Boufous
About Ilias Boufous
Ilias Boufous is a Quantitative Analyst specializing in Active Equity at HSBC, where he automates data streams and applies machine learning for portfolio strategies. He has a background in software development and financial data analysis, with previous roles at notable institutions including Société Générale and Groupe Crédit Agricole.
Work at HSBC
Ilias Boufous currently holds the position of Quantitative Analyst in Active Equity within the Front Office at HSBC. He has been with the organization since 2023. In this role, he focuses on automating large-scale data streams using cloud technology, enabling real-time data analysis. His work involves collaborating with asset managers to build and monitor thematic model-based portfolios, enhancing financial models and strategies.
Previous Experience
Before joining HSBC, Ilias Boufous worked at several notable organizations. He served as a Solution Architect for Open Banking at Société Générale from 2022 to 2023. Prior to that, he was a Research and Development Engineer in Financial Data at Groupe Crédit Agricole from 2021 to 2022. He also gained experience as a Software Developer at Sorbonne Université from 2020 to 2021 and as a Full Stack Developer and Data Analyst at Sayari in 2021.
Education and Expertise
Ilias Boufous has a strong educational background in computer science and business informatics. He earned a Bachelor's degree in Computer Science from Sorbonne Université, which he completed in 2022. He then pursued two Master's degrees at Université Paris Dauphine - PSL, achieving a Master's in Business Informatics (MIAGE - M1) in 2023 and currently working towards a Master's in Financial Intelligence (MIAGE - M2), expected to complete in 2024.
Technical Skills
Ilias Boufous specializes in leveraging machine learning to develop innovative portfolio strategies. His technical expertise includes navigating complex data architecture to enhance financial models and implementing sustainable financial solutions using ESG criteria. His role requires a deep understanding of data analysis and automation technologies, particularly in cloud computing.