About our group:

Since 1979, Seagate has been creating precision-engineered data storage technologies that deliver superior capacity, speed, safety, and performance. We are a diverse workforce of 40,000 creative, hard-working, passionate people all over the world—Silicon Valley, the Southeast Asia, India, China, the United Kingdom, and beyond. At Seagate, we know that data is always in motion, alive, connected—and we harness it in order to maximize human potential.

About the role - you will:

• Developed and validated end‑to‑end quality anomaly detection methods using statistical, clustering, ML‑based, and time‑series techniques (z‑score, IQR, outlier detection).
• Enable automated, consistent, and scalable visual inspection using AI to detect defects, anomalies, or patterns that humans miss or cannot do fast enough.
• Assist in benchmarking anomaly detection approaches against current engineering rules (e.g., red/yellow dot sweeps, column swipes).
• Partner with quality engineers to drive process efficiency improvements.
• Driving AI adoption to automate routine tasks and improve operational efficiency.

About you:

You are a self-motivated and independent learner with a strong communication and UX storytelling mindset. You enjoy working in teams and translating complex data into actionable insights.

Your experience includes:

• Strong background in statistics and machine learning (regression, clustering, classification, anomaly/outlier detection).
• Experience integrating OpenAI APIs (text and vision models) into internal tools, analytics pipelines, or inspection workflows.
• Proficiency in Python (pandas, scikit-learn, PyOD, stats models) or KNIME workflows.
• Experience designing and developing interactive dashboards using Power BI and Tableau.
• Good problem-solving and analytical mindset; ability to handle large datasets efficiently.
• Currently pursuing a Bachelor’s or master’s degree in IT, Computer Science, or other Engineering majors

Location:

Location: Korat Thailand
Travel: None