Description

You will own data science initiatives for manufacturing and industrial environments, focusing on predictive maintenance and process optimization.

This role is on-site.

Responsibilities

• Build and deploy predictive models for maintenance, quality, and yield improvement.
• Analyze time-series sensor data and operational datasets using industrial analytics tools.
• Conduct statistical modeling and hypothesis-driven analysis to drive root-cause investigations.
• Develop Python-based solutions for anomaly detection and regression tasks.

Required Skills

• 5+ years of experience in Data Science or Advanced Analytics.
• Hands-on experience in manufacturing, industrial, or plant environments.
• Strong proficiency in Python (Pandas, NumPy, Scikit-learn).
• Expertise with Seeq (industrial analytics platform) for time-series analysis.
• Strong SQL skills for data extraction and manipulation.
• Deep understanding of machine learning techniques including regression and anomaly detection.
• Bachelor's degree in a quantitative field.

Key Skills

Education

Bachelor's degree