Gert De Geyter

About

I am a machine learning lead with over 10 years of experience leading data science and engineering teams on a broad range of AI and ML projects. I love to talk about A.I. both on a technical level and a non-technical level for organizations like TEDx or Datacamp. I still have a strong connection to academia and work as a guest professor at Columbia University where I teach several AI related classes. If you have any questions feel free to contact me: ✉ [email protected] ✆ +13479872104

Experience

• AI Staff Engineer at Teragonia
  Aug 2025 - Present · 11 mos

• Guest Professor at Columbia University School of Professional Studies
  Jan 2023 - Present · 3 yrs 6 mos

  I teach courses within the Applied Analytics Master program. Columbia University’s Master of Science in Applied Analytics prepares students with the practical data and leadership skills to succeed. The program combines in-depth knowledge of data analytics with the leadership, management, and communication principles and tactics necessary to impact decision-making at all levels within organizations.

• Deloitte Consulting (10 yrs 6 mos)
  • Machine Learning Lead
    Oct 2018 - Jun 2025 · 6 yrs 9 mos

  • Manager Data Analytics
    Jan 2015 - Oct 2018 · 3 yrs 10 mos

• Invited Professor: Programming in Python and Machine learning at Toulouse School of Economics
  Dec 2016 - Dec 2023 · 7 yrs 1 mo

  A course given to the 2nd Master Econometrics and Empirical Economics introducing the basics of Python, functional and object-oriented programming. The second part of the course focusses on machine learning using Pandas, basic and interactive data visualisation.

• Invited Professor: Programming in Python and Machine learning at IAE Toulouse, Toulouse 1 Capitole university school of management
  Jan 2017 - Jan 2023 · 6 yrs 1 mo

  A course given to the 2nd Master Financial Markets and Risk Evaluation (FiRE) and Finance and Information Technology (FIT) introducing the basics of Python, functional and object-oriented programming. The second part of the course focusses on machine learning using Pandas, basic and interactive data visualisation and application to modelling the price of an European call options using the analytical Black-Scholes approach and a Monte-Carlo approach using geometric brownian motion.