Internship/Graduation: Data-Driven Service - Millions of Logs, One Insight: Can You Find It?

Internship/Graduation: Data-Driven Service – Millions of Logs, One Insight: Can You Find It?

Assignment type: Internship/Graduation

Start date: September 2025

Assignment duration: 6 – 12 months

Location: Veghel

Education level: Master

Desired study: Computer Science, Data Science, Industrial Engineering, or related

Language: English

Description of assignment

At Vanderlande, we are transforming the way we manage service operations by integrating data-driven insights into our service operations. The ongoing “Service Insights” project aims to proactively detect anomalies and predict anomalies in material handling process using machine learning and real-time data analysis. While we’ve built a series of Splunk-based dashboards and data models, we’re now seeking an intern to dive deeper into these tools, validate their accuracy, and explore untapped opportunities for optimization and predictive maintenance. A key research question for this assignment is: How can we evolve existing analytics and machine learning models into intelligent, self-learning systems that not only detect anomalies in real time but also anticipate future failures with high confidence, enabling zero downtime operations in high-volume logistics environments?

Department description

You will be part of the Service Insights project team within the Amazon Dedicated Service Desk department. The team consists of AI-engineers, Splunk experts, Process engineer and system architects, working closely with FSC engineers and product owners. Our work focuses on building real-time analysis tools, machine learning models, and visualization dashboards that support proactive service decisions. You will collaborate in an agile team setup, working on actual production data and tooling used globally across Amazon Parcel sites.

Tasks/responsibilities

• Validate and explore existing Splunk dashboards used for real-time log analysis.
• Identify patterns and correlations in logs that lead to failures.
• Propose and implement enhancements or new dashboard modules.
• Research and experiment with anomaly detection and predictive maintenance algorithms.
• Present findings and recommendations in clear, actionable formats to the team.

Your profile

• Knowledge of A.I., Machine Learning (especially anomaly detection techniques), scripting (e.g., Python).
• Familiarity with Splunk, Databricks, Pyspark, and Azure Cloud is preferred.
• Strong foundation in Python, SQL, and data visualization.
• Interest in generative AI and its potential for log interpretation is a plus.
• Basic knowledge of industrial systems/PLC SCADA is a plus.
• Curious mindset with analytical thinking and hands-on approach to problem solving.
• *Mandatory enrolment to a Dutch Education System & resident of The Netherlands.

For more information, contact us by e-mail: internship@vanderlande.com.