At Aon, a Data Analyst is at the core of the firm's mission to shape decisions for the better. Aon is a leading global professional services firm providing a broad range of risk, retirement, and health solutions. In this role, you do not just crunch numbers; you translate complex risk, insurance, and financial data into strategic insights that help multinational corporations and institutions protect and grow their businesses.

Your work directly impacts Aon’s proprietary data platforms, client-facing dashboards, and consultative risk models. Whether you are analyzing market trends to optimize reinsurance strategies, evaluating health benefit portfolios, or building predictive models to mitigate commercial risk, your analytical output is highly visible. This role sits at the intersection of business intelligence, data engineering, and strategic consulting, making it both technically demanding and highly impactful.

Working as a Data Analyst at Aon requires a unique blend of technical execution and business acumen. You will collaborate closely with brokers, risk consultants, and product managers to solve ambiguous, real-world problems. The scale of Aon's global operations means you will work with massive, diverse datasets, requiring robust data hygiene practices and an analytical mindset that looks beyond the data points to find the underlying business story.

To succeed in the Data Analyst interview process at Aon, you must prepare for a blend of highly technical questions, statistical theory, and structured behavioral inquiries. The questions are designed to test your technical competency, your logical approach to problem-solving, and your cultural fit within a global professional services environment.

Technical & Mathematical Concepts

These questions assess your foundational knowledge of statistics, programming efficiency, and predictive modeling.

• Explain the difference between supervised and unsupervised machine learning, and give an example of how you would apply each to risk assessment.
• How do you handle missing or collinear data in a regression model?

Preparing for an interview at Aon requires a structured approach that balances technical mastery with professional communication. You should treat the interview process as a consultative discussion, demonstrating not just your ability to write code or calculate formulas, but your ability to drive business value.

Role-related knowledge – You must demonstrate a strong command of data manipulation tools, statistical analysis, and data visualization. Aon values candidates who can write clean, efficient Python and SQL code and who understand the mathematical principles behind the models they build.

Problem-solving ability – Interviewers will evaluate how you approach ambiguous business problems. You should focus on structuring your thoughts logically, breaking complex problems down into testable hypotheses, and explaining your methodology step-by-step.

Communication & Stakeholder Management – Because Data Analysts at Aon frequently interface with business leaders and consultants, your ability to translate complex data insights into clear, actionable business recommendations is critical.

Cultural Alignment & Adaptability – Aon operates in a highly collaborative, fast-paced corporate environment. You need to show that you are a supportive team player, open to feedback, and capable of navigating the professional standards of a global enterprise.

The interview process for a Data Analyst at Aon typically spans three main stages, though the exact structure can vary slightly depending on your geographic location and the specific business unit. The process is designed to evaluate both your technical capabilities and your collaborative style.

Initially, you will undergo a screening phase, which may be conducted by an internal recruiter or a third-party talent partner. This conversation is focused on understanding your professional background, your career motivations, and your general fit for the role. Following this, the process moves into a rigorous evaluation of your technical skills, often involving a deep dive into statistics, Python, and machine learning concepts with hiring managers and senior analysts. The final stage typically involves conversations with directors or senior leadership to evaluate your strategic thinking, communication, and alignment with Aon's core values.

This visual timeline illustrates the typical progression from the initial outreach to the final decision. You should use this framework to pace your preparation, focusing first on high-level behavioral and technical fundamentals, before diving deep into advanced mathematical concepts and case studies for the manager rounds.

To stand out in the Aon interview process, you must excel in three core evaluation areas.

Statistical and Mathematical Foundations

Aon's business is built on risk mitigation and financial forecasting, which means your statistical knowledge must be airtight. Interviewers will test your understanding of probability distributions, regression analysis, and predictive modeling.

Be ready to go over:

• Probability Distributions – Understanding normal, binomial, and Poisson distributions and how they apply to risk modeling.
• Hypothesis Testing – Formulating null hypotheses, calculating p-values, and understanding Type I and Type II errors.
• Regression Modeling – The mathematical assumptions behind linear and logistic regression and how to validate them.
• Advanced concepts (less common) – Bayesian statistics, time-series forecasting, and survival analysis for risk duration.

Example questions or scenarios:

• "How would you mathematically prove that a specific variable is a statistically significant predictor of insurance claim frequency?"
• "Explain how you would use a random forest model to predict client churn, and how you would evaluate its performance compared to a logistic regression model."

Python and Technical Execution

You will be expected to demonstrate your coding proficiency, particularly in Python, as well as your ability to manipulate data efficiently using SQL and pandas.

Be ready to go over:

• Data Wrangling – Merging, filtering, and transforming messy datasets in Python.
• Feature Engineering – Creating predictive features from raw data inputs.
• SQL Optimization – Writing complex queries, utilizing window functions, and optimizing join performance.

Example questions or scenarios:

• "Write a SQL query to identify the top 10% of clients by total premium value across multiple regions."
• "How would you optimize a Python script that is running out of memory when processing a multi-gigabyte dataset?"

Behavioral and Professional Motivation

Aon values candidates who are proactive, resilient, and highly aligned with the firm's strategic goals. You must be able to articulate why you want to build a career at Aon and how you handle the pressures of a corporate environment.

Be ready to go over:

• Client Focus – Demonstrating how your analysis directly supports client satisfaction and decision-making.
• Collaboration – Showcasing your ability to work effectively across diverse, cross-functional teams.
• Conflict Resolution – Discussing how you navigate professional disagreements or project setbacks.

Example questions or scenarios:

• "Describe a time when a project requirement changed mid-way through your analysis. How did you adapt your approach?"
• "Why are you interested in the risk and retirement consulting sector, and why do you believe Aon is the right place to apply your analytical skills?"