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Curriculum Vitae
Education
Master 2 Random Modeling (M2MO, ex DEA Laure Elie) — Université Paris Cité, Paris
Sept. 2026 – Present
Master in Mathematics and Applications — Université Paris Dauphine – PSL, Paris
Sept. 2025 – Present
Licence in Mathematics and Data Science — Faculty of Science and Engineering, Sorbonne University, Paris
Highest honors
Experience
Market Risk Analyst (Apprenticeship) — BNP Paribas CIB, Paris
September 2026 – Present | Equity Derivatives
Research assistant intern — École Normale Supérieure (LATTICE), Paris
April 2026 – August 2026 | NLP and machine learning
Analyzed trends in generative AI and agentic systems across research and learning practices. Collected and structured data from Euraxess, AcademicJobs, and French PhD theses databases. Investigated knowledge collapse dynamics and their implications for academic work, cooperation, and knowledge production.
Data Scientist Intern — Center for Genomic Regulation (CRG), Barcelona
April 2025 – August 2025 | Statistics and HPC
Analyzed genomic datasets with Bioconductor and performed computation heavy tasks on HPC clusters. Integrated Machine Learning models for cancer gene inference in non-coding regions. Designed a reproducible statistical validation workflow to strengthen result reliability.
Data Scientist Intern — Sifra Tech, Paris
July 2024 – March 2025 | Deep Learning
Developed Kernel U-Net, a Python library and network architecture for sequential data. Implemented the State Space Model and variants (S4, Mamba) in KUN, improving model performance. Analyzed embeddings and batch sampling to improve training stability and generalization.
Activities and Academic Projects
Superconductivity Critical Temperature Prediction
May 2026 | statistical learning, regression, Python
Built a reproducible pipeline to predict superconductors' critical temperature from 81 physical and chemical features. Compared OLS, Ridge, Lasso, k-NN, and gradient boosting; selected k-NN based on held-out RMSE.
IMC Prosperity 3 Trading Challenge
April 2025 | algorithmic trading, statistical arbitrage, Python
Designed statistical arbitrage algorithms combining models and order-book liquidity signals. Ranked 214th globally out of 12,620 teams, 16th in France.
Huawei Tech Arena 2024
December 2024 | control theory, Kalman filter
Implemented a Kalman filter-based algorithm for battery state-of-charge estimation. Awarded the Bronze Prize (2 000€) at Huawei Tech Arena 2024, Nuremberg.
Skills
Data analysis, reporting, and BI: Statistical analysis, data preparation and exploration, data visualization, Power BI dashboards, linear models, time series; SQL, Python (pandas, NumPy), R (tidyverse, ggplot2), advanced Excel, VBA
Quantitative modeling and finance: Optimization, numerical simulation with Monte Carlo methods, stochastic processes, derivatives, portfolio management, algorithmic trading, statistical arbitrage
Machine Learning and Deep Learning: scikit-learn, PyTorch, TensorFlow/Keras, JAX; supervised learning, sequential architectures.
Programming and technical environments: Python, R, MATLAB, JavaScript/TypeScript, HTML/CSS; Git, Linux/Bash, workflow automation, Jupyter, Conda, LaTeX
Scientific computing and infrastructure: HPC/Slurm, parallel computing, reproducible workflows, containers, client-server environments, local deployment of AI tools
Languages
French (fluent) · English (fluent — TOEFL 99, TOEIC 900) · Chinese (native) · German (A2) · Spanish (A1)
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