Looking for a job

Chelsy Mena

@chelsymena

Message

I build machine learning systems that turn complex data into operational tools.

France

Message

What I'm looking for

I'm looking to build machine learning and data products that solve real operational or clinical problems, combining rigorous modeling with deployment, analytics, and measurable business impact.

I'm developing machine learning models at Inria and Université Paris-Saclay to estimate Pulse Wave Velocity from clinical photoplethysmogram signals. My work investigates the domain-generalization gap between synthetic and real clinical data using PCA, KDE, adversarial classification, and model benchmarking.

Previously at Andercol (AkzoNobel), I built and deployed a CNN-based defect-detection system with OpenCV and Dash, reducing evaluation time from half a day to half an hour and helping secure $120M COP in government funding. I also delivered an LLM-powered customer portal, ETL pipelines, and more than 20 real-time dashboards and web applications.

My projects span computer vision, NLP, conversion prediction, clustering, and interpretable cancer detection. I work across Python, SQL, deep learning, cloud data platforms, and data visualization, and I enjoy bringing research and operational data products together.

Experience

Work history, roles, and key accomplishments

Current

Machine Learning Research Intern

Current

Inria / Universite Paris-Saclay

Mar 2026 - Present (6 months)

Developing a machine learning model to estimate Pulse Wave Velocity from photoplethysmogram signals using clinical datasets. Diagnosed domain-generalization gaps between synthetic and clinical data using PCA, KDE, and adversarial classification.

Machine Learning Deep Learning PCA KDE Adversarial Classification Python

Data Analyst

Andercol (AkzoNobel)

Aug 2021 - Aug 2024 (3 years)

Built and deployed a CNN-based computer vision model for automated defect detection, cutting evaluation time from half a day to half an hour. Designed and deployed an LLM-powered customer portal and maintained ETL pipelines feeding real-time dashboards.

Python SQL OpenCV Dash Streamlit Azure Data Factory Databricks Power BI ETL Computer Vision LLM OpenAI API

Education

Degrees, certifications, and relevant coursework

Universite Jean Monnet

Master of Science, Computer Science

2024 -

Activities and societies: M1 (Mention Bien – 15/20): Machine Learning, Data Analysis, Introduction to AI, Advanced Algorithms, Complexity Theory, Optimization, Data Mining, Computer Vision. M2 (Grades not yet available): Advanced Machine Learning, Optimization, PAC-Bayes Theory, Deep Learning, Probabilistic Graphical Models, Data Mining.

Pursuing an MSc in Computer Science with a focus on Machine Learning and Data Mining, with coursework in advanced machine learning, deep learning, and optimization.