Mrs. Camille Lefevre, Ms. | Ms.Lefevre

Camille Lefevre is a data scientist and researcher based in Lyon, France. She earned her M.S. in Machine Learning from École Normale Supérieure in 2018. With over five years of experience, Camille specializes in machine learning algorithms, statistical learning, and predictive modeling for data-driven decision-making.
Her professional work includes designing, implementing, and evaluating machine learning models for diverse applications in industry and research. Camille has contributed to multiple research publications and applies best practices in data preprocessing, feature engineering, model selection, and performance evaluation. She focuses on leveraging data science to uncover insights, optimize processes, and support evidence-based decision-making.
Camille follows a rigorous, research-driven methodology in her work, emphasizing reproducibility, interpretability, and model robustness. She collaborates with multidisciplinary teams to integrate machine learning solutions into real-world applications, ensuring practical and ethical use of data.

Camille Lefevre is a data scientist from France with 5+ years of experience in machine learning, predictive modeling, and statistical learning.

Camille applies a structured, research-focused methodology in data science, including iterative model development, performance validation, and reproducibility checks. She ensures models are interpretable, robust, and ethically applied in practical scenarios.