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komiayi/README.md

Komi Ayi

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 analytics, BI dashboarding, behavioral data, and predictive modeling.

Full portfolio →

Currently open to data science and statistics roles.

Research

**Master's thesis (UQAM, 2025) — supervised by Prof. Karim Oualkacha with co-supervision by Prof. Geneviève Lefebvre:
Analyse de médiation causale pour des médiateurs non causalement liés.
Read on Archipel UQAM → · Companion R Shiny app: rbcm →

Featured projects

COVID-19 Québec dashboard – Wave-by-wave analysis

Power BI · Power Query (M) · Public health analytics

Power BI dashboard analyzing the evolution of COVID-19 in Québec across 7 waves + endemic period (Feb. 2020 – Sep. 2023), using INSPQ open data. Built on a star schema with two reusable parameterized M functions handling the tricky source structure (duplicate column names, sex encoded in headers, position-dependent indicators). Fully reproducible — loads data directly from INSPQ URLs.

Ligue 1 strategic forecasting engine

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.

→ Try the live app

Mediation analysis with unmeasured confounding

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.

Waze churn prediction

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.

Tech stack
Languages Python · R · SQL
Python Pandas · NumPy · Scikit-Learn · SciPy · Matplotlib · Streamlit
R dplyr · tidyr · caret · ggplot2 · rpart · randomForest
BI Power BI · Power Query (M) · DAX · Tableau
Tools SQLiteStudio · Git

Certifications

Google Advanced Data Analytics (Professional Certificate) · Introducing DAX · Create a dashboard with Tableau

Get in touch

LinkedIn Email Portfolio

Pinned Loading

  1. covid-19-quebec-powerbi covid-19-quebec-powerbi Public

    Power BI dashboard analyzing COVID-19 in Québec across 7 waves + endemic period, using INSPQ open data.

  2. rbcm rbcm Public

    An R Shiny application for causal mediation analysis when mediators are correlated but not causally linked.

    R 1

  3. dna_mediation dna_mediation Public

    Causal mediation analysis under unmeasured confounding between correlated mediators. Application: childhood trauma → DNA methylation → cortisol stress reactivity. (R, Master's research)

    R 1

  4. churn-waze-prediction churn-waze-prediction Public

    Predicting Waze user churn with three tree-based models (Decision Tree, Random Forest, XGBoost), with class-imbalance handling and decision-threshold optimization. Final XGBoost recall = 0.64.

    Jupyter Notebook 1

  5. regression-trees-ensemble-methods regression-trees-ensemble-methods Public

    Comparative study of regression trees, Bagging, and Random Forests focusing on MSE and stability. Friedman simulation (J=1000) + real-world application to Tehran apartment construction costs. Gradu…

    R 1

  6. MixLaw MixLaw Public

    R package implementing an S3 class for probability distribution mixtures, with methods for sampling, density visualization, and basic descriptive statistics. Developed for MAT8186 (UQAM).

    R 1