António Correia
About António Correia
António Correia is a Senior Data Scientist at Feedzai, where he focuses on fraud prevention strategies. He has a diverse background in economics and data science, having previously worked in banking supervision at the Bank of Portugal.
Current Role at Feedzai
António Correia currently serves as a Senior Data Scientist at Feedzai, a position he has held since 2021. In this role, he focuses on leveraging data science techniques to enhance fraud prevention strategies. His work involves applying advanced analytical methods to detect and mitigate fraudulent activities, contributing to the company's mission of ensuring secure financial transactions.
Previous Experience at Feedzai
Before his current position, António worked at Feedzai as a Data Scientist from 2019 to 2021. During this time, he developed and implemented data-driven solutions aimed at improving fraud detection methodologies. His contributions during this period laid the groundwork for his subsequent advancement to a senior role.
Experience at Bank of Portugal
António Correia has a significant background in banking supervision, having worked at the Banking Prudential Supervision Department of the Bank of Portugal. He began as an intern from 2014 to 2015 and later served as an Advisor from 2015 to 2019. His experience in this department provided him with a strong foundation in financial regulation, which informs his current work in data-driven fraud prevention.
Educational Background
António holds multiple degrees in economics and data science. He earned a Bachelor's degree from Nova School of Business and Economics, where he studied Banking, Financial Regulation, and Supervision. He also studied at Tilburg University, obtaining a Master's degree in Economics. Additionally, he completed a Postgraduate Degree in Enterprise Data Science & Analytics at NOVA IMS Information Management School, further enhancing his expertise in data science.
Skills and Expertise
António Correia possesses a unique combination of skills in both economics and data science. His professional background allows him to integrate insights from these fields to improve fraud detection methodologies. His strong foundation in financial regulation enables him to approach data-driven fraud prevention with a comprehensive understanding of the regulatory landscape.