Expériences professionnelles
Research assistant
Brown University Health
De Janvier 2026 à Mars 2026
Bachelor Thesis on « Predicting Phase III Oncology Trial Outcomes from Design Features »
Supervised by Jeremy L. Warner, MD, MS, FAMIA, FASCO at the Legorreta Cancer Center.
Trading exotics eqd
BNP PARIBAS
De Juin 2025 à Août 2025
Summer internship
- Assisted in pricing and risk analysis of exotic equity derivatives using internal models and market data
- Supported traders with daily P&L monitoring, trade booking, and ad hoc analysis on structured products
Research assistant
CNRS
De Février 2025 à Août 2025
Co-author of “Stochastic Modeling of Telomere Shortening and Reconstruction” (with M. Kimmel, M. Doumic & T. Texeira), presented at:
- American Mathematical Society (JMM 2026), Washington, D.C., January 2026
- 38th M. Smoluchowski Symposium on Statistical Physics, Kraków, Poland, September 2025
- 10th International Conference on Risk Analysis (ICRA10), Patras, Greece, September 2025
- Intelligent Systems for Molecular Biology / European Conference on Computational Biology (ISMB/ECCB), Liverpool, July 2025
Manuscript in preparation, submission and publication planned for 2026
Data analyst - data engineer
Planète Mer
De Août 2024 à Septembre 2024
I contributed to major conservation projects, including BioLit, PELA-Méd, and Marha, focusing on ecological data analysis and reporting for marine biodiversity conservation.
Key Responsibilities:
-Data Extraction and Transformation: Developed Python scripts using Pandas to extract, clean, and transform large datasets ensuring data accuracy and consistency for analysis.
-Geospatial Data Integration: Leveraged GeoPy to enrich datasets with geospatial information, applying geocoding and reverse geocoding to ensure precise location-based data.
-Taxonomic Data Integration: Augmented biological data from BioLit by integrating taxonomic databases, ensuring accurate species identification and categorization.
-Fisheries Data Analysis: Analyzed fisher participation data across zones and seasons in the PELA-Méd project, along with CPUE (Catch Per Unit Effort) trends for sea urchin fishing in the Var region.
-Data Visualization and Reporting: Created visualizations with Python (Matplotlib, Numpy), summarizing trends over multiple years to support decision-making in marine conservation.
-Collaborative Reporting: Delivered high-quality visual reports that helped shape conservation strategies and informed stakeholders about marine biodiversity trends.
Skills: Python | Pandas | GeoPy | Numpy | Data Extraction | Data Wrangling | Data Analysis | Excel | Matplotlib | Statistical Modeling | Ecological Research | Conservation Reporting
Formation complémentaire
M.S. in Data Science
Harvard University - Data Science and Statistics
2026 à 2028
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