Résumé
With a Master’s in Statistics from EPFL (graduating with 5.5/6), I am passionate about applying statistical modeling, quantitative methods, and data science to solve complex, real-world challenges. My expertise spans regression analysis, Bayesian statistics, time series modeling, machine learning, and stochastic processes, with applications in finance, biostatistics, business analytics, and scientific research. What I do best: -Develop statistical models to uncover patterns, predict outcomes, and optimize decision-making. -Apply advanced probability methods to quantify uncertainty and assess risks in complex systems. -Use machine learning techniques to enhance predictive accuracy and automate data-driven processes. -Perform large-scale data analysis, handling high-dimensional datasets with efficiency. -Conduct rigorous hypothesis testing to validate statistical assumptions and drive robust conclusions. -Develop time series models to forecast trends, detect anomalies, and analyze temporal dependencies. -Implement Bayesian methods to integrate prior knowledge and improve inference in uncertain environments. -Create impactful visualizations to communicate complex findings clearly and effectively. -Translate mathematical insights into actionable business or research strategies. -Effectively communicate technical insights to both expert and non-expert audiences.
Expériences professionnelles
Research intern
EPFL
De Mars 2024 à Août 2024
-Conducted research on the validation of rainfall generators' extremal behavior using Extreme Value Theory.
-Applied statistical models, including Generalized Extreme Value (GEV) and Generalized Pareto Distribution (GPD), to analyze rainfall data.
-Worked as part of a multidisciplinary team of researchers to ensure accuracy in climate and hydrometeorological simulations.
-Created a research poster to present my findings to the Mathematics section at EPFL, effectively communicating key insights.
-Gained expertise in data analysis, statistical modeling and interdisciplinary collaboration for research.
Internship - quantitative trading camp
Jane Street
De Octobre 2023 à Octobre 2023
-Selected to join a competitive program exploring real-world applications of mathematics and probability in quantitative trading.
-Engaged in interactive group activities, mock trading sessions, and lectures on topics such as probability, market structure, and arbitrage.
-Gained insight into the diverse roles within Jane Street and enhanced my understanding of financial markets and quantitative strategies.
R&d master trainee in statistics
Nestlé
De Septembre 2023 à Février 2024
During my six-month internship at the Nestlé Research Center as an R&D Master Trainee in Statistics, I focused on applying advanced statistical modeling and programming techniques to complex data from clinical trials. A significant part of my work involved developing efficient algorithms and R code to compute the fragility index, a metric used to assess the robustness of clinical trial outcomes. I also contributed to exploratory data analysis and created statistical models to analyze and interpret diverse datasets.
In addition to working on clinical data, I applied my skills in data visualization using R and various libraries like ggplot2 to create insightful graphics for decision-making. This internship gave me hands-on experience with statistical programming, hypothesis testing, regression analysis, and large-scale data processing, allowing me to enhance my expertise in quantitative methods and advanced statistical techniques.
This experience strengthened my ability to design and implement data-driven models, improve workflow efficiency, and contribute to innovative research within a dynamic, interdisciplinary team.
Research intern
Aalto University
De Janvier 2022 à Juin 2022
-Conducted a statistical analysis of cryptocurrency data, focusing on Bitcoin and Dogecoin returns over time.
-Applied statistical tests to evaluate the significance of differences in returns, highlighting Dogecoin's higher profitability in specific periods.
-Leveraged the Central Limit Theorem to validate assumptions and ensure robust analysis.
-Developed skills in data analysis, statistical modeling, and applying mathematical theory to real-world financial data.
Private tutor
De Septembre 2020 à Octobre 2024
As a private tutor, I help students excel in mathematics across various levels, from high school to university. I provide personalized support in probability, statistics, algebra, analysis, optimization, and machine learning. Over the years, I’ve worked with around 40 different students, aged 12 to 40, tailoring my approach to fit their unique learning needs.
This experience has taught me how to effectively convey complex mathematical concepts to individuals with varying levels of mathematical background, making advanced topics accessible to those who may not have a deep understanding of the subject.
Teaching assistant
EPFL (École polytechnique fédérale de Lausanne)
De Septembre 2020 à Juillet 2023
As a Teaching Assistant at EPFL, I supported students in understanding and mastering complex concepts across various mathematics courses. My role involved helping students from different promotions navigate challenging topics, assisting them with lectures, and guiding them through their exercises.
Parcours officiels
Langues
Anglais - Courant
Français - Langue maternelle
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