Data Science / AI Adoption Intern

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