Primary Details

Time Type: Full time

Worker Type: Employee

At QBE, our purpose is to give people the confidence to achieve their ambitions inside and outside of work. From development opportunities to flexible work options and highly competitive reward and benefits packages, we understand the importance of living our values when it comes to our people. Everything we do at QBE is underpinned by our company’s cultural elements – because we know it's not just what we do that matters, it's how we do it that makes the difference.

This opportunity is accountable for supporting modeling and data science for assigned business areas contributing to the scientific integrity of work products, including study design, research methodology, and deployment of statistical approaches and modelling. Works under immediate supervision with a focus on learning and professional development.

Past example intern projects involve machine learning models supporting fraud detection and pricing segmentation, as well as model deployment and governance.

Primary Responsibilities

• Build foundational knowledge of feature sets and gain exposure to machine learning algorithms

• Gain experience and work with analytics partners to build and put models into production, quantify and analyze model performance; guide and oversee model refreshing requirements

• Make key contributions to fit-for-purpose analytics tools and infrastructure that will be used by the end user (e.g. claims handler or underwriter) and contribute to Information Technology strategy Network with other members of the department to establish mutual respect in business processes

• Participate in weekly training sessions

• Clearly communicate results of projects to technical and non-technical staff and present to entire actuarial and data science department

Required Qualifications

• Completion of High School Diploma/GED

• Full-time current enrollment in a bachelor’s or master’s degree program in Data Science, Data Engineering, Data Analytics, Actuarial Science, Mathematics, Computer Science or other quantitative fields

• Must be returning to college/university upon completion of internship

• Course work or relevant experience with demonstrated achievements

• Ability to work from June 2nd, 2025 to August 8th, 2025

Preferred Competencies/Skills

• Programming Proficiency: Strong programming skills in: Python, R, or Julia for data manipulation and model development.

• Mathematical Proficiency: Strong mathematical foundation in calculus, probability, and linear algebra.

• Statistical Analysis: Solid understanding of statistical concepts and techniques for data analysis.

• Machine Learning: Experience with machine learning algorithms such as regression, classification, clustering, and gradient boosting.

• Data Visualization: Ability to create clear and insightful data visualizations using tools like Matplotlib, Seaborn, or ggplot2.

• Problem-Solving: Proven ability to break down complex problems and apply data science solutions.

• Critical Thinking: Strong analytical and critical thinking skills to interpret data and derive meaningful insights.

• Collaborative Attitude: Willingness to work in a team environment and contribute to collaborative projects.

• Communication Skills: Effective communication of technical findings to non-technical stakeholders.

• Adaptability: Willingness to learn and adapt to new data science techniques and tools

Preferred Knowledge

• Data Manipulation: Proficiency in data manipulation libraries such as Pandas and NumPy.

• Machine Learning Libraries: Familiarity with machine learning libraries such as Scikit-Learn, TenserFlow, or PyTorch

• Probability and Statistics: Understanding or probability distributions, hypotheses testing, and statistical inference

• SQL: Knowledge of SQL for querying and extracting data from databases

• Sofware Engineering Practices: Understanding of fundamental software engineering principles such as version control (e.g., Git), code documentation, modular coding, and collaborative coding workflows to ensure maintainable and scalable data science projects

About QBE

We can never really predict what’s around the corner, but at QBE we’re asking the right questions to enable a more resilient future by helping those around us build strength and embrace change to their advantage. We’re an international insu