Skills
Technical & domain expertise
Every skill listed is grounded in shipped code, published work, or real-world impact. No self-assessment percentages — only what I've proven in production.
Machine learning & AI
Implemented, trained, and deployed across banking, energy, social-media analytics, and forecasting systems.
PyTorch
Scikit-learn
XGBoost
LightGBM
CatBoost
Transformers (Hugging Face)
SHAP (model explanation)
Conformal prediction
Survival analysis (lifelines)
Time-series forecasting
LangChain / agentic AI
Uncertainty quantification
Statistics & econometrics
Mastered at ISSEA-CEMAC; applied in research and production settings.
Generalized Linear Models (GLMs)
Regression analysis
Panel data methods
Fixed-effects models
Survival modelling
Bayesian inference
Probabilistic forecasting
Causal inference
Natural language processing
Focused on low-resource and African languages; published at ACL SemEval-2026.
Multilingual NLP
Low-resource language systems
Transformer fine-tuning
Class imbalance handling
Adaptive Focal Loss
Text classification
Sentiment & polarization detection
Tools, frameworks & deployment
Production-ready coding, version control, and deployment practices.
Python (primary)
R (statistical computing)
Stata (econometrics)
Streamlit (dashboarding)
Git / GitHub (version control)
LaTeX (academic writing)
Jupyter Notebooks
Numba (parallelization)
ODK & CSPro (data collection)
Domain expertise
Deep experience in sectors where ML meets real business risk.
Banking & financial services
Enterprise risk & survival modeling
Energy systems & grid forecasting
Agricultural resilience
Policy-oriented data science
Explainable AI for high-stakes decisions
Human-AI collaboration
Languages
French (native speaker)
English (working proficiency, fluent written & spoken)