Gabriel Nogueira
Intern at BNP Paribas Personal Finance- Claim this Profile
Click to upgrade to our gold package
for the full feature experience.
Topline Score
Bio
Experience
-
BNP Paribas Personal Finance
-
France
-
Banking
-
700 & Above Employee
-
Intern
-
Apr 2022 - Present
As part of the Business Performance team, worked on the enhancement of predictive Machine Learning tools used for preparing outbound marketing campaigns. • Focus on enhancing ensemble learning algorithms already in use. • Also took part on the elaboration of A/B test for telemarketing campaigns. As part of the Business Performance team, worked on the enhancement of predictive Machine Learning tools used for preparing outbound marketing campaigns. • Focus on enhancing ensemble learning algorithms already in use. • Also took part on the elaboration of A/B test for telemarketing campaigns.
-
-
-
Université Paris Dauphine - PSL
-
France
-
Higher Education
-
700 & Above Employee
-
Master M2
-
Oct 2020 - Present
Student at MASEF program focused on financial mathematics. Student at MASEF program focused on financial mathematics.
-
-
-
Deutsche Bank
-
Germany
-
Financial Services
-
700 & Above Employee
-
Intern
-
May 2021 - Aug 2021
Studied the use of Reinforcement Learning techniques for Market Making on ETF’s. The main approaches considered for solving the problem were TD (Temporal Difference) Learning and the use of Actor-Critic Algorithms. The study was mainly based on simulations. • Project based on the work of Castello Branco (2018). • Use of core machine learning modules for Python: Pytorch and Pandas. • Practical data analysis problems such as price-diffusion calibration. Studied the use of Reinforcement Learning techniques for Market Making on ETF’s. The main approaches considered for solving the problem were TD (Temporal Difference) Learning and the use of Actor-Critic Algorithms. The study was mainly based on simulations. • Project based on the work of Castello Branco (2018). • Use of core machine learning modules for Python: Pytorch and Pandas. • Practical data analysis problems such as price-diffusion calibration.
-
-
-
École Polytechnique
-
France
-
Research Services
-
700 & Above Employee
-
Diplôme d'Ingénieur
-
Jan 2017 - Oct 2020
- Major at Applied Mathematics - Major at Applied Mathematics
-
-
-
BOREAL SAS
-
France
-
Aviation and Aerospace Component Manufacturing
-
1 - 100 Employee
-
Estagiário
-
Jun 2018 - Aug 2018
Assisted the company's team in a study for the development of a net recovery system for their drone, allowing it to be fully operated from vessels. - Reviewed literature and analyzed analogue systems already in use on the market. - Carried out a statistical study on the drone’s stability during flight. - Determined the fundamental dimensions for the net recovery system. Assisted the company's team in a study for the development of a net recovery system for their drone, allowing it to be fully operated from vessels. - Reviewed literature and analyzed analogue systems already in use on the market. - Carried out a statistical study on the drone’s stability during flight. - Determined the fundamental dimensions for the net recovery system.
-
-
Education
-
Université Paris Dauphine - PSL
Master M2, Applied Mathematics -
École Polytechnique
Diplôme d'Ingénieur, Applied Mathematics