Willis Towers Watson Data Analyst Interview Questions + Guide in 2025
Overview
Willis Towers Watson is a leading global advisory, broking, and solutions company that empowers clients to turn risk into a path for growth.
As a Data Analyst at Willis Towers Watson, you will be pivotal in analyzing data to provide actionable insights that drive business decisions and improve operational efficiency. You will collaborate with stakeholders across various departments to understand reporting requirements, utilizing your SQL skills to extract and manipulate data from databases. Your role will involve developing and maintaining interactive dashboards and reports, primarily using tools like Power BI, to monitor key performance indicators and business metrics. Strong analytical skills will be essential for conducting ad-hoc analysis and data modeling to address specific business questions. A commitment to improving data quality and accessibility is also vital, as you will work to ensure reliable reporting and analytics. This position demands a detail-oriented individual with excellent communication skills, capable of supporting end-users in interpreting reports and dashboards.
This guide will help you prepare for your interview by highlighting key areas of focus, ensuring you can articulate your relevant experiences and demonstrate your fit for the role within the company's collaborative and data-driven culture.
Willis Towers Watson Data Analyst Interview Process
The interview process for a Data Analyst position at Willis Towers Watson is structured to assess both technical and interpersonal skills, ensuring candidates are well-suited for the collaborative and analytical nature of the role. The process typically unfolds in several key stages:
1. Initial Phone Interview
The first step is a 30 to 45-minute phone interview with a recruiter. This conversation serves as an introduction to the company and the role, allowing the recruiter to gauge your interest and fit for the position. Expect to discuss your background, relevant experiences, and motivations for applying to Willis Towers Watson.
2. Skills Assessment
Following the initial interview, candidates may be required to complete a skills assessment. This often includes an Excel test to evaluate your proficiency with data manipulation and analysis, as well as a basic math test to assess your quantitative skills. Additionally, a mental arithmetic test may be included to further gauge your numerical aptitude.
3. Competency-Based Interview
The next stage involves a competency-based interview, where you will be asked to elaborate on your CV, discuss your skill sets, and explain why you are interested in the Data Analyst role. This interview focuses on your analytical abilities, problem-solving skills, and how you handle various work situations, including stress management and teamwork.
4. Technical Interview
In this round, you will engage with a panel of interviewers, which may include team members and managers. The focus will be on your technical skills, particularly your experience with SQL and data visualization tools like Power BI. Be prepared to discuss specific projects you've worked on, the methodologies you employed, and the outcomes of your analyses.
5. Final Interview
The final interview is typically a more in-depth discussion with senior management or team leads. This stage may involve situational questions that assess your ability to collaborate with stakeholders, your understanding of business intelligence, and your approach to improving data quality and accessibility. This is also an opportunity for you to ask questions about the team dynamics and company culture.
As you prepare for these interviews, it's essential to familiarize yourself with the specific tools and methodologies relevant to the Data Analyst role at Willis Towers Watson. Next, let's delve into the types of questions you might encounter during the interview process.
Willis Towers Watson Data Analyst Interview Questions
In this section, we’ll review the various interview questions that might be asked during a Data Analyst interview at Willis Towers Watson. The interview process will likely assess your analytical skills, technical proficiency, and ability to communicate insights effectively. Be prepared to demonstrate your knowledge of data analysis tools, SQL, and your understanding of business metrics.
Technical Skills
1. Can you explain the process you follow when analyzing a dataset?
Understanding your analytical process is crucial for this role, as it reflects your ability to derive insights from data.
How to Answer
Outline your approach, including data cleaning, exploratory data analysis, and the methods you use to draw conclusions. Mention any tools or techniques you prefer.
Example
“I typically start by cleaning the dataset to remove any inconsistencies or missing values. Then, I perform exploratory data analysis to understand the data's structure and identify patterns. Finally, I apply statistical methods or machine learning models to derive insights and present my findings using visualization tools like Power BI.”
2. What SQL functions do you find most useful for data analysis?
This question assesses your SQL proficiency, which is essential for extracting and manipulating data.
How to Answer
Discuss specific SQL functions you frequently use, such as JOINs, GROUP BY, and aggregate functions. Provide examples of how you’ve applied them in past projects.
Example
“I often use JOINs to combine data from multiple tables, which helps in creating a comprehensive view of the data. The GROUP BY function is also crucial for summarizing data, especially when analyzing key performance indicators. For instance, I used it to aggregate sales data by region to identify trends.”
3. Describe a time when you had to present complex data findings to a non-technical audience.
Communication skills are vital for a Data Analyst, especially when conveying insights to stakeholders.
How to Answer
Share a specific instance where you simplified complex data into understandable insights. Highlight your approach to tailoring your presentation to the audience's level of understanding.
Example
“In my previous role, I presented a complex analysis of customer behavior to the marketing team. I created visualizations that highlighted key trends and used analogies to explain the data. This approach helped the team grasp the insights quickly and apply them to their strategies.”
Problem-Solving
4. How do you handle missing or incomplete data in your analysis?
This question evaluates your problem-solving skills and your approach to data integrity.
How to Answer
Discuss the techniques you use to address missing data, such as imputation, exclusion, or using algorithms that can handle missing values.
Example
“When I encounter missing data, I first assess the extent and impact of the missing values. Depending on the situation, I might use imputation techniques to fill in gaps or exclude those records if they are not significant. I always document my approach to ensure transparency in my analysis.”
5. Can you give an example of a project where you improved data quality?
This question assesses your experience with data governance and quality assurance.
How to Answer
Describe a specific project where you identified data quality issues and the steps you took to resolve them.
Example
“In a previous project, I noticed discrepancies in our sales data due to inconsistent data entry practices. I initiated a data quality audit, implemented standardized data entry protocols, and trained the team on best practices. As a result, we saw a significant improvement in data accuracy, which enhanced our reporting capabilities.”
Business Acumen
6. How do you determine which metrics are most important for a business?
This question gauges your understanding of business metrics and their relevance to decision-making.
How to Answer
Explain your approach to identifying key performance indicators (KPIs) based on business objectives and stakeholder needs.
Example
“I start by collaborating with stakeholders to understand their goals and challenges. From there, I identify metrics that align with those objectives, ensuring they are actionable and relevant. For instance, in a recent project, I focused on customer retention rates as a key metric to help the marketing team refine their strategies.”
7. What tools do you use for data visualization, and why?
This question assesses your familiarity with data visualization tools and your ability to present data effectively.
How to Answer
Discuss the tools you are proficient in and the reasons for your preference, such as ease of use, functionality, or integration capabilities.
Example
“I primarily use Power BI for data visualization due to its user-friendly interface and robust features. It allows me to create interactive dashboards that make it easy for stakeholders to explore the data. I also appreciate its integration with SQL databases, which streamlines my workflow.”
Behavioral Questions
8. How do you prioritize your tasks when working on multiple projects?
This question evaluates your time management and organizational skills.
How to Answer
Describe your approach to prioritization, including any tools or methods you use to manage your workload effectively.
Example
“I prioritize my tasks based on deadlines and the impact of each project on the business. I use project management tools like Trello to keep track of my tasks and ensure I allocate time effectively. Regular check-ins with my team also help me stay aligned with project goals.”
9. Describe a challenging situation you faced in your previous role and how you overcame it.
This question assesses your resilience and problem-solving abilities.
How to Answer
Share a specific challenge, your thought process in addressing it, and the outcome of your actions.
Example
“In my last role, we faced a tight deadline for a major report due to unexpected data issues. I quickly organized a team meeting to delegate tasks and focused on the most critical analyses. By collaborating closely and working overtime, we managed to deliver the report on time, which was well-received by management.”