Nolan Albanet

Nolan Albanet

Analyste Quantitatif @ Deriv

About Nolan Albanet

Nolan Albanet is a quantitative analyst at Deriv, where he has worked since 2022 in Paris, France. He holds multiple degrees in mathematics and statistics from prestigious institutions, including a Master 2 from École normale supérieure and Paris Dauphine - PSL University.

Work at Deriv

Nolan Albanet has been employed at Deriv as an Analyste Quantitatif since 2022. His role involves quantitative analysis, contributing to the company's data-driven decision-making processes. Based in Ville de Paris, Île-de-France, France, he applies his mathematical expertise to enhance the company's analytical capabilities.

Education and Expertise

Nolan Albanet has a strong educational background in mathematics and applied mathematics. He completed his Bachelor’s degree at Sainte-Geneviève School, focusing on Mathematics and Physics, from 2017 to 2019. He furthered his studies at École normale supérieure, earning a Master 1 (M1) in Mathematics in 2021, followed by a Master 2 (M2) in Applied Mathematics in 2022. Additionally, he obtained a Master 2 (M2) in Mathematics and Statistics from Paris Dauphine - PSL University in the same year. He also holds a Bachelor’s degree in Mathematics from Paris-Saclay University, completed in 2020.

Background

Nolan Albanet has a diverse academic background that includes significant experience in mathematics. He interned at the Institut des Hautes Études Scientifiques - IHES in 2020, where he worked in a Mathematics Laboratory for four months. This experience provided him with practical exposure to advanced mathematical concepts and research methodologies.

Achievements

Nolan Albanet has achieved multiple academic qualifications in mathematics and applied mathematics. His educational journey includes completing several degrees, including Bachelor’s and Master’s programs, which reflect his commitment to the field. His internship at IHES further demonstrates his engagement with mathematical research and analysis.

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