Data Intern

At Workwize, we’re helping IT teams to easily equip their remote and global teams with all necessary IT equipment. Our automated SaaS platform simplifies hardware deployment, management, and retrieval with fast, reliable deliveries in 100+ countries.

With 50.000 users and 120.000 devices under management, we’re solving hybrid work challenges like laptop deliveries, returns and equipment tracking, allowing IT teams to focus less on manual hassles and more on strategic initiatives.

Join our team to help shape the future of global collaboration. At Workwize, your work will make a real impact in building smarter, more connected workplaces worldwide.

LinkedIn has also recognized Workwize as one of the Top 10 Startups for 2025 in the Netherlands!

About the Role 

As a Data & AI Intern, you'll sit at the intersection of Data & Analytics and Service Operations. You'll help build the data infrastructure and AI-powered automations that drive how we make decisions and run our operations day to day.
You'll work hands-on with our data warehouse, build and refine dashboards that leadership and service teams rely on, and develop AI workflows that take real work off people's plates. It's a chance to turn messy operational data into clear insight and to ship automations that have immediate, visible impact.
You'll be trusted with ownership from day one, in a fast-paced environment where your work directly shapes how we operate and scale.  

Key responsibilities

• Data modeling & infrastructure. Build and maintain SQL models in BigQuery across delivery, procurement, retrieval, and warehouse performance, following our layered modeling conventions.
• Dashboards & reporting. Develop and iterate on internal dashboards that surface the metrics that matter, and help translate data into decisions in recurring walkthrough sessions with service owners.
• AI & automation. Build and refine our AI-powered workflows, including owning improvements to our Customer Support AI, and identify new areas where automation can create leverage.
• Operational analysis. Dig into operational questions, from SLA performance to carrier and supplier data, and turn the findings into clear recommendations.

Skills and qualifications
•    Completed BSc and currently in the final stages of a master's, or already holding a master's, in a quantitative or STEM field (e.g. Econometrics, Data Science, or a related discipline).
•    Comfortable with SQL, or a strong eagerness to learn it quickly; familiarity with a data warehouse (BigQuery a plus) is a bonus.
•    Strong analytical and problem-solving skills; you enjoy working with data to draw insights and support decisions.
•    Curiosity about AI and LLMs, and ideally some hands-on experience building with them or with automation tools. •    Clear written and verbal communication, with the ability to structure complex ideas simply. •    Highly organized and detail-oriented, able to manage multiple priorities and meet deadlines. •    Experience in startups, consulting or operations is a strong plus.