Job Description

The Advanced Applications Experts (AAE) team serves Seagate Supply Chain Finance by designing and deploying automation and analytics that reduce cycle time, improve accuracy, and strengthen compliance. We co-create solutions with finance and operations, embedding governance and traceability in every workflow. Our culture is rooted in psychological safety, inclusion, and continuous learning together.

About the role - you will:


As Advanced Applications Experts (AAE) intern, help transform Supply Chain Finance with compliant automation, predictive analytics, and scenario modeling. Learn-by-doing in a safe, inclusive environment while building real solutions our stakeholders use every month:

  • Build automation and analytics prototypes (Python, SQL, notebooks) that streamline Finance reporting and close processes.

  • Develop scenario models (incl. regression) to test assumptions, quantify sensitivities, and generate decision-ready insights.

  • Contribute to data architecture and strategy—data sourcing, modeling, lineage, and governance for reusable analytics assets.

  • Instrument solutions with metrics (time-savings, error rates, adoption) and create clear documentation for scale-out.

  • Partner with Finance stakeholders to run discovery, define success criteria, and validate outcomes in real workflows.

  • Participate in “Show & Share” forums and learning circles in a safe, supportive environment.

    • About you:

  • Curious, analytical, and comfortable experimenting in public psychological safety matters to you.

  • Bias to action with attention to detail; you seek feedback and iterate quickly.

  • Collaborative communicator who can explain technical ideas to non-technical partners.

  • Integrity-first mindset: you treat compliance, security, and data ethics as part of the design.

  • Ability to turn ambiguous business questions into data problems with measurable outcomes.

    • Your experience includes:

  • Currently pursuing bachelor’s in Data Science, Computer Science, business analytics or any relevant fields

  • Experience in working statistics and machine learning linear/logistic regression, feature engineering, model evaluation in projects

  • Working knowledge of Python (pandas, scikit-learn), SQL, and data visualization (Power BI/Tableau or similar).

  • Experience building scenario models (sensitivity analysis, what-if simulations) using notebooks or BI tools.

    • Location:


    Our Woodlands site is one of the largest electronics manufacturing sites in Singapore, housing our recording media operations. Spread over three sites, it is easily accessible via bus or from the MRT Station, with many employees taking mass transportation to work. Here at work, you can enjoy breakfast, lunch, dinner, and snacks at our onsite canteen and coffee shop. We offer a range of facilities including an in-house gym and dance studio, as well as after-work badminton and table tennis competitions. On-site celebrations and community volunteer opportunities also abound. 

    Location: Woodlands, Singapore, W3

    Travel: None

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