At QBE, we believe machine learning and AI can transform the insurance industry - making it smarter, faster, and more human
Requirements
- Working knowledge of Python; ability to quickly learn new Python packages and programming concepts
- 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
Responsibilities
- 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
Other
- Current enrollment in a Bachelor’s in Computer Science, Engineering, Mathematics, Data Science, or a related field
- Strong communication skills and a collaborative mindset
- Eagerness to learn and grow - technically and professionally
- Applicants must be authorized to work in the United States on a full-time basis without the need for current or future sponsorship
- This position is not eligible for visa sponsorship
