Reliability Data Scientist (Maternity Cover) — AI for Semiconductors

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

Job summary

STMicroelectronics, Italy, is seeking a data science professional to develop AI/ML models and analytics to improve semiconductor quality and reliability. You will build predictive solutions, integrate diverse data sources, and translate insights into actionable recommendations for cross-functional teams.

The role requires a Master’s degree in a quantitative field, strong programming skills, and experience with AI/ML and analytics tools.

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, predictive modeling, and data visualization.
• Good understanding of semiconductor technologies; reliability knowledge is a plus.

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

AI/ML experience

Analytics

Education

Master’s degree in quantitative field

Tools

pandas

NumPy

scikit-learn

XGBoost

PyTorch

TensorFlow

Job description

STMicroelectronics, Italy, is seeking a data science professional to develop AI/ML models and analytics to improve semiconductor quality and reliability. You will build predictive solutions, integrate diverse data sources, and translate insights into actionable recommendations for cross-functional teams.

The role requires a Master’s degree in a quantitative field, strong programming skills, and experience with AI/ML and analytics tools.