AI-Driven Reliability Data Scientist — Maternity Cover

STMicroelectronics Italia; Agrate Brianza; On-site; EUR 38,000 - 45,000; Full time

Job summary

STMicroelectronics Italia is seeking a data science professional to develop AI/ML models and advanced analytics to improve semiconductor quality and reliability. You will build predictive solutions for anomaly detection for failure patterns, integrate data from test, manufacturing and field returns, and translate findings into actionable insights through statistics and visualization.

Collaboration with product, quality, manufacturing and customer teams is essential.

Qualifications

• Master’s degree in a quantitative field.
• Strong programming skills.
• Experience with AI/ML and analytics tools (pandas, NumPy, scikit-learn, XGBoost, PyTorch, TensorFlow).
• Solid knowledge of statistics and data visualization.
• Knowledge of semiconductor technologies; reliability engineering is a plus.
• Strong communication and cross-functional collaboration.

Responsibilities

• Develop AI/ML models and advanced analytics to improve semiconductor quality and reliability.
• Build predictive solutions for anomaly detection, failure pattern recognition, and early risk identification.
• Integrate data from test, manufacturing, field returns, and reliability sources into scalable analytical workflows.
• Translate complex data into actionable insights through statistical modeling, explainable AI, and visualization.
• Collaborate across product, quality, manufacturing, process, and customer teams to support root-cause analysis and decision-making.
• Contribute to reliability metrics, data standards, and monitoring dashboards.

Skills

Strong programming skills

AI/ML experience

Statistics

Data visualization

Cross-functional collaboration

Education

Master’s degree in a quantitative field

Tools

Pandas

NumPy

scikit-learn

XGBoost

PyTorch

TensorFlow

Job description

STMicroelectronics Italia is seeking a data science professional to develop AI/ML models and advanced analytics to improve semiconductor quality and reliability. You will build predictive solutions for anomaly detection for failure patterns, integrate data from test, manufacturing and field returns, and translate findings into actionable insights through statistics and visualization.

Collaboration with product, quality, manufacturing and customer teams is essential.