Statistician · Data Scientist · Research & Innovation
Master's in applied statistics with a specialization in causal modeling for health research. I focus on rigorous methodology and decision-oriented data analysis, with applied work spanning public health, behavioral data, and predictive modeling.
Currently open to data science and statistics roles.
Master's thesis (UQAM, 2025) — supervised by Prof. Karim Oualkacha:
Analyse de médiation causale pour des médiateurs non causalement liés.
Read on Archipel UQAM → ·
Companion R Shiny app: rbcm →
Python · Scikit-Learn · Streamlit
Multinomial logistic regression model predicting match outcomes for the 2025–2026 French Ligue 1, deployed as an interactive Streamlit dashboard. Processes offensive efficiency and defensive resilience metrics to output win/draw/loss probabilities.
R · Causal inference · Biostatistics
Research project on the effect of childhood trauma on cortisol stress reactivity, mediated by DNA methylation. Implements advanced statistical methods to correct for bias arising when mediators share an unmeasured common cause. A companion R Shiny tool — rbcm — implements these methods interactively.
Python · Random Forest · XGBoost
End-to-end churn modeling pipeline including feature engineering, dynamic threshold optimization for F1 maximization, and feature-importance interpretation of the best-performing model.
More projects (regression trees & ensemble methods, MixLaw R package…) available in the portfolio.
| Languages | Python · R · SQL |
| Python | Pandas · NumPy · Scikit-Learn · SciPy · Matplotlib · Streamlit |
| R | dplyr · tidyr · caret · ggplot2 · rpart · randomForest |
| Tools | Tableau · SQLiteStudio · Git |
Google Advanced Data Analytics (Professional Certificate) · Introducing DAX · Create a dashboard with Tableau