Data Science Intern (Summer 2026)

Title: Data Science and Machine Learning Engineering Intern (Summer 2026)

The Opportunity: At QBE, we believe machine learning and AI can transform the insurance industry – making it smarter, faster, and more human. Our Data Science and Machine Learning Engineering team builds real-world solutions that support Pricing, Underwriting and Claims, driving innovation and impact across the business. We value curiosity, clarity, craftsmanship, and collaboration – and we’re looking for team members who share these values.
As an intern, you’ll contribute to building and deploying ML and AI systems that solve practical business problems. This role is ideal for someone eager to apply technical skills, learn from experienced peers, and grow in a fast-paced, supportive environment.

• Location: Sun Prairie, Wisconsin
• Work Arrangement: This role is hybrid, where you will be expected to be in the office 4 days per week at our Sun Prairie, WI office

• The salary range for this role is between $18-$27.00 an hour

Your new role

• Use data to uncover insights that improve underwriting and operations.
• Build and evaluate models, explore new features, and collaborate with teams to deliver measurable impact.
• Contribute to the development and maintenance of deployment pipelines, ensuring models are robust, reproducible, and scalable.
• Write clean, efficient, and well-documented Python code using libraries such as pandas, numpy, pydantic, and FastAPI.
• Learn and apply modern ML tools and frameworks such as Transformers and MLflow.
• Stay curious – ask questions, seek feedback, and continuously improve your skills.

Required Qualifications

• Current enrollment in a Bachelor’s in Computer Science, Engineering, Mathematics, Data Science, or a related field.
• Working knowledge of Python; ability to quickly learn new Python packages and programming concepts.

Preferred Competencies/Skills

• Proficiency in Python and familiarity with core data science libraries (e.g., pandas, numpy, scikit-learn).
• Exposure to cloud platforms (especially Azure) and containerization tools like Docker.
• Understanding of MLOps concepts such as Git, CI/CD, and model lifecycle management.
• Familiarity with model validation and monitoring practices.
• Strong communication skills and a collaborative mindset.
• Eagerness to learn and grow – technically and professionally.

Why QBE? What if you could have a positive impact – at work and in the world?

At QBE, we’re enabling a more resilient future – for our customers, communities, environment, and for our people. We’re building momentum to achieve something significant and know our people are at the center of our success.

Our industry offers interesting and varied careers where you can help people to protect what matters most. As part of the QBE team, you’ll get to spend every day working with people who are passionate, talented and kind. And our international scale means we’re big enough for your ambitions, yet small enough for you to make a real impact.

Join us now, so you can be part of our success – and we can be part of yours!

https://www.linkedin.com/company/qbe-north-america/

QBE is committed to providing reasonable accommodation to, among others, individuals with disabilities and disabled veterans. If you need an accommodation because of a disability to search and apply for a career opportunity with QBE, please inform our Talent Acquisition team to let us know the nature of your accommodation request and your contact information.

Equal Employment Opportunity:

QBE provides equal employment opportunities to applicants and employees without regard to race; color; gender; gender identity; sexual orientation; religious practices and observances; national origin; pregnancy, childbirth, or related medical conditions; protected veteran status; or disability or any other legally protected status.

This position is not eligible for visa sponsorship. Applicants must be authorized to work in the United States on a full-time basis without the need for current or future sponsorship.

Supplementary information