Timea Kovacs

Timea Kovacs has an extensive work experience spanning over multiple industries. Timea most recently served as the Head of Data Science at Cynet Security since July 2022. Prior to that, they held the position of VP AI & Data Science at a stealth technology startup in venture capital financing from February 2021 to July 2022. From December 2017 to December 2021, Timea worked as the Chief Technology Officer and Head of Data Science and Engineering at Correlor Technologies.

Before transitioning to technical roles, Timea worked as a Data Scientist at CrediFi from March 2015 to December 2017. Timea also had a period of self-employment from August 2012 to February 2015, where they specialized in web development and marketing solutions.

Timea's early career includes roles at the Ministry of Finance, where they served as the Economic Forecasting Team Leader from October 2011 to July 2012 and as a Statistician and Economic Analyst from September 2005 to September 2011. Additionally, they worked as an Economic Researcher at the OECD Economics Department from June 2010 to December 2010. Timea started their professional journey as an Economic Journalist at Sanoma Media - Online Division, where they worked from 2001 to 2004.

Timea Kovacs began their education in 1998 and graduated in 2003 with a Master of Science (M.Sc.) in Economics with Research from Corvinus University of Budapest. Timea then pursued their PhD studies in Mathematical Economics at Corvinus University of Budapest from 2007 to 2012. In 2004, they obtained a Master of Science (M.Sc.) in Economics, specializing in Macroeconomics - Monetary Economics and Financial Institutions, from the University of Amsterdam. Timea also attended the Budapest School for Central Bank Studies in 2011, but the degree obtained is unspecified. In the same year, they completed the RYT-200 Yoga Teacher certification in Vinyasa Flow - Hatha Yoga from YogaWorks.

Timea Kovacs has also obtained additional certifications, including "DevOps for Data Scientists" from LinkedIn in June 2018 and "Neural Networks and Deep Learning" from Coursera in December 2017.