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Регистрация: 27.08.2026

Caleb Djarabé

Специализация: Data Analysis
— Junior Data Scientist with a background in economics and applied mathematics (linear algebra, calculus, statistics) and hands-on experience in Python, SQL, and Machine Learning. — Experience in applied research, data analysis, predictive modeling, time series, and visualization, with clear communication of results. — Delivered Data Science projects applied to economic data, notably macroeconomic forecasting and analysis of UEMOA indicators.
Python SQL Git GitHub API rest api Excel Power BI Azure pandas Data Analysis Machine Learning FastAPI Docker MySQL CI/CD methodologies Tableau Linux Bash
— Junior Data Scientist with a background in economics and applied mathematics (linear algebra, calculus, statistics) and hands-on experience in Python, SQL, and Machine Learning. — Experience in applied research, data analysis, predictive modeling, time series, and visualization, with clear communication of results. — Delivered Data Science projects applied to economic data, notably macroeconomic forecasting and analysis of UEMOA indicators.
Python SQL Git GitHub API rest api Excel Power BI Azure pandas Data Analysis Machine Learning FastAPI Docker MySQL CI/CD methodologies Tableau Linux Bash

Портфолио

Machine Learning Project

Data Science / ML Internship Program (Elevvo Internship) — 10 tasks from Level 1 to Industry Level: regression, clustering, classification, recommendation systems, audio deep learning, time series, object detection (YOLOv8), predictive maintenance, and complete MLOps pipeline (FastAPI + Docker + CI/CD).

Prévision macroéconomique

Plateforme de prévision macroéconomique automatisée pour l'UEMOA (Afrique de l'Ouest), couvrant inflation, PIB, taux de change, masse monétaire, balance commerciale et secteurs d'activité pour plusieurs pays (Sénégal, Côte d'Ivoire, Burkina Faso, Mali). Le pipeline complet va de l'ingestion automatisée des données (via l'API DBnomics/BCEAO) à la modélisation par séries temporelles (SARIMA), avec prévisions 2026-2027 à intervalle de confiance, backtesting et analyse de corrélations entre indicateurs. Les résultats sont présentés via un dashboard interactif (React/Recharts, déployé sur Vercel) incluant export des données (CSV/JSON/PDF), page méthodologie détaillant sources et limites, comparateur multi-pays, score de vulnérabilité économique composite, et version bilingue français/anglais.

AnalystLab Internship

Data Science internship at AnalystLab Africa (remote program, 2 months), structured around concrete case studies for fictitious client scenarios. Analysis of employee attrition from the IBM HR Analytics dataset to identify the factors driving staff departures, followed by in-depth feature engineering and preprocessing work on a loan approval dataset (Loan Prediction): handling missing values, encoding categorical variables, creating new predictive variables, advanced statistical exploration and correlation analysis to prepare the data for modeling.

Скиллы

Python
SQL
Machine Learning
Data Analysis
Pandas
NumPy
Scikit-learn
Power BI
FastAPI
Docker
Git
GitHub
Matplotlib
Seaborn
Plotly
Streamlit
Time Series Forecasting
YOLOv8
CI/CD
Statistics
Linear Algebra
ETL
MySQL
SQLite
Jupyter Notebook
Data Cleaning
Data Visualization
K-Means
Exploratory Data Analysis
SARIMA

Опыт работы

Machine Learning Intern
08.2026 - 08.2026 |Elevvo Pathways
ML
A collection of 10 machine learning projects covering the entire spectrum of the field: prediction and regression, unsupervised clustering, multi-class classification on unbalanced data, collaborative filtering recommendation systems, audio classification, time series forecasting, object detection using computer vision (YOLOv8), and industrial predictive maintenance. The final project deploys a model to production via a FastAPI, containerized with Docker and integrated into an automated CI/CD pipeline. Each project includes an exploratory data analysis, training and comparison of several models, and a clear summary of the results.
Data Scientist Intern
08.2026 - 10.2026 |AnalystLab Africa
Python, Pandas, NumPy, Matplotlib, Seaborn, Jupyter Notebook
● Conducted exploratory data analysis on the IBM HR Analytics dataset (1,470 employees, 35 variables) to identify key factors associated with employee attrition. ● Analyzed the impact of age, monthly income, overtime, department, and job role on employee retention. ● Produced visualizations and statistical analyses using Python, Pandas, NumPy, Matplotlib, and Seaborn in Jupyter Notebook. ● Formulated initial insights to inform future predictive attrition analyses.

Образование

Financial Engineering (Магистр)
с 2026 - По настоящий момент
WorldQuant University
Economics (Бакалавр)
2020 - 2023
Université St. Charles Lwanga

Языки

ФранцузскийРоднойАнглийскийСредний