Looking for a job

matteo pozzan

@matteopozzan

Data Scientist with experience building production-ready machine learning solutions, predictive models, and data-driven applications.

Italy

Message

What I'm looking for

I’m seeking long-term remote Data Scientist or Machine Learning roles compatible with working from Ecuador, via either international employment or a contractor arrangement.

I'm a Data Scientist with 3+ years of experience building production-ready machine learning solutions and data-driven applications. I take projects from business problem definition through model development, deployment, and production monitoring.

My experience includes predictive modeling, time-series forecasting, statistical learning, Bayesian optimization, and ML monitoring. I've developed scalable ML workflows, optimization pipelines, and monitoring tools using Python, SQL, AWS, MLflow, and Metaflow.

At The Goodyear Tire & Rubber Company, I co-developed an AutoML forecasting framework that reduced top-level MAPE from 20% to 5% while cutting execution time from 24 hours to 30 minutes. I also built a Bayesian optimization workflow that improved a precision-weighted F-score from 0.70 to 0.90 and developed Streamlit dashboards for KPI reporting, model performance monitoring, drift detection, and data quality analysis.

Experience

Work history, roles, and key accomplishments

Educational Support Worker

Engim Ong

Jul 2025 - Jul 2026 (1 year)

Supported children and adolescents through tailored tutoring and educational activities in a resource-constrained environment. Collaborated daily with local staff in Spanish to improve cross-cultural communication and problem-solving.

Cross Cultural Communication Problem Solving Spanish Leadership

Associate Data Scientist

The Goodyear Tire & Rubber Company

Jan 2023 - Jun 2025 (2 years 5 months)

EMEA Sales Forecasting
• Co-developed a Metaflow-based AutoML forecasting framework supporting EMEA sales and supply-chain planning by automating model selection and hierarchical allocation across countries and product segments. Reduced top-level MAPE from 20% to 5% and execution time from 24 hours to 30 minutes. The solution was also adopted by the Supply Chain team for distribution planning.

Git Time Series Transfer Learning XGBoost Data Science Streamlit Anomaly Detection Optuna Pandas Machine Learning Bayesian Optimization Statistical Modeling Python ARIMA NumPy Data Visualization Metaflow SQL

Data Scientist Intern

The Goodyear Tire & Rubber Company

Mar 2022 - Sep 2022 (6 months)

Conducted a theoretical and experimental study on the minimum sample size required to train robust machine-learning models, analyzing its impact on predictive performance, stability, and generalization. The research became the foundation of my Master’s thesis in Data Science.