Arthur J. Gallagher & Co. Business Intelligence Interview Guide

Getting ready for a Business Intelligence interview at Arthur J. Gallagher & Co.? The Arthur J. Gallagher & Co. Business Intelligence interview process typically spans a wide range of question topics and evaluates skills in areas like data analysis, dashboard development, business metrics, data storytelling, experimental design, and communication with non-technical stakeholders. At this global insurance and risk management firm, Business Intelligence professionals are responsible for transforming raw data into actionable insights that drive strategic decision-making and operational improvements. Typical projects may involve designing scalable dashboards, analyzing customer or operational data, and presenting complex findings to diverse audiences in a way that influences business outcomes and aligns with the company’s commitment to client service and data-driven solutions.

In preparing for the interview, you should:

• Understand the core skills necessary for Business Intelligence positions at Arthur J. Gallagher & Co.
• Gain insights into Arthur J. Gallagher & Co.’s Business Intelligence interview structure and process.
• Practice real Arthur J. Gallagher & Co. Business Intelligence interview questions to sharpen your performance.

At Interview Query, we regularly analyze interview experience data shared by candidates. This guide uses that data to provide an overview of the Arthur J. Gallagher & Co. Business Intelligence interview process, along with sample questions and preparation tips tailored to help you succeed.

Arthur J. Gallagher & Co. is a global leader in insurance brokerage, risk management, and consulting services, serving clients across more than 150 countries. The company specializes in delivering tailored solutions for commercial, personal, and employee benefit risks, helping organizations manage uncertainty and protect their assets. Gallagher is known for its commitment to ethical practices, client-centric service, and fostering a collaborative culture. As a Business Intelligence professional, you will support data-driven decision-making and process improvements that enhance Gallagher’s ability to deliver innovative risk management solutions to its clients.

As a Business Intelligence professional at Arthur J. Gallagher & Co., you will be responsible for transforming complex data into actionable insights that support strategic decision-making across the organization. You will develop and maintain data models, dashboards, and reports, collaborating with teams such as finance, operations, and risk management to identify trends and optimize business processes. Core tasks include gathering requirements, analyzing performance metrics, and presenting findings to stakeholders to drive operational efficiency and improve client outcomes. This role is essential in helping Gallagher leverage data to enhance its insurance and risk management services, contributing directly to the company’s growth and client-focused mission.

2.1 Stage 1: Application & Resume Review

The process begins with a thorough review of your application and resume by the business intelligence hiring team. They assess your experience with data warehousing, dashboard design, and analytics, as well as your ability to communicate actionable insights and work with complex datasets. Candidates with a proven track record in building BI solutions, optimizing data pipelines, and presenting data to both technical and non-technical audiences stand out. To prepare, ensure your resume highlights relevant business intelligence projects, quantifiable impact, and proficiency with data visualization and ETL tools.

2.2 Stage 2: Recruiter Screen

Next, a recruiter will conduct a phone or video screen to evaluate your motivation for joining Arthur J. Gallagher & Co., your understanding of the business intelligence role, and your overall fit for the company culture. Expect to discuss your career trajectory, interest in the insurance and risk management industry, and your approach to collaborating with cross-functional teams. Preparation should focus on articulating your professional journey, aligning your values with the company’s mission, and demonstrating clear communication skills.

2.3 Stage 3: Technical/Case/Skills Round

This stage typically involves one or two interviews with BI team members or managers, where you’ll tackle technical and case-based scenarios. You may be asked to design a data warehouse, propose metrics for a dashboard, or solve problems involving data quality, ETL pipeline architecture, and business health metrics. Emphasis is placed on your ability to model business processes, analyze user journeys, and recommend data-driven changes to improve organizational outcomes. Prepare by reviewing your experience with SQL, data modeling, dashboard creation, and discussing how you’ve addressed messy datasets or implemented new analytics solutions.

2.4 Stage 4: Behavioral Interview

The behavioral round is designed to assess your interpersonal skills, leadership potential, and adaptability in a fast-paced environment. Interviewers may ask you to describe how you’ve resolved conflicts, presented complex insights to non-technical stakeholders, or navigated challenges in data projects. They will be looking for examples that demonstrate your ability to communicate with clarity, collaborate across departments, and drive business impact through actionable intelligence. Practice sharing specific stories that highlight your strengths and how you’ve overcome obstacles in previous roles.

2.5 Stage 5: Final/Onsite Round

The final round typically consists of multiple interviews with business intelligence leadership, analytics directors, and potential cross-functional partners. These sessions may include a technical presentation, a deep dive into a past BI project, and situational questions about designing scalable BI solutions, optimizing marketing channel metrics, or evaluating the effectiveness of a new product feature. You’ll also be evaluated on your strategic thinking, ability to influence decision-makers, and readiness to contribute to company-wide initiatives. Preparation should involve rehearsing presentations, anticipating high-level business questions, and demonstrating your expertise in delivering measurable results.

2.6 Stage 6: Offer & Negotiation

If successful, you’ll move to the offer and negotiation stage, where the recruiter will discuss compensation, benefits, and team placement. This stage is typically handled by HR and may include a conversation with the hiring manager to finalize details and answer any remaining questions about the role or expectations. Be prepared to negotiate based on your experience and the value you bring to the business intelligence function.

2.7 Average Timeline

The typical interview process for a Business Intelligence role at Arthur J. Gallagher & Co. spans 3-5 weeks from initial application to final offer. Fast-track candidates with strong business analytics and communication skills may progress in as little as 2-3 weeks, while most applicants experience about a week between each stage. Scheduling for technical and onsite interviews can vary based on team availability and candidate preferences.

Now, let’s explore the types of interview questions you may encounter throughout the process.

3.1. Data Analysis & Experimentation

Business Intelligence at Arthur J. Gallagher & Co. relies heavily on robust analytical skills to guide strategic decisions and optimize operations. Expect questions that assess your ability to design experiments, interpret results, and recommend actionable insights using real-world data.

3.1.1 You work as a data scientist for ride-sharing company. An executive asks how you would evaluate whether a 50% rider discount promotion is a good or bad idea? How would you implement it? What metrics would you track?
Discuss how you would design an experiment, select control and treatment groups, and identify relevant metrics such as customer acquisition, retention, and profitability. Explain how you’d analyze results and communicate findings to stakeholders.

3.1.2 The role of A/B testing in measuring the success rate of an analytics experiment
Describe how you would set up an A/B test, define success criteria, and ensure statistical rigor. Emphasize the importance of sample size, randomization, and interpreting results for business impact.

3.1.3 How would you measure the success of an online marketplace introducing an audio chat feature given a dataset of their usage?
Explain which KPIs you’d analyze (e.g., engagement, conversion, retention), how you’d segment users, and what statistical methods you’d apply to assess feature impact.

3.1.4 *We're interested in how user activity affects user purchasing behavior. *
Outline your approach to correlating activity metrics with purchasing outcomes. Discuss regression analysis, cohort studies, and how you’d control for confounding factors.

3.1.5 How would you present the performance of each subscription to an executive?
Focus on summarizing churn rates, lifetime value, and retention trends. Highlight the importance of clear visualizations and concise storytelling tailored to executive priorities.

3.2. Data Quality & Engineering

Data quality is foundational for reliable analytics at Arthur J. Gallagher & Co. Candidates should be ready to discuss their experience with data cleaning, pipeline design, and maintaining data integrity in complex environments.

3.2.1 How would you approach improving the quality of airline data?
Describe your process for profiling data, identifying common issues, and implementing cleaning or validation routines. Highlight your experience with automation and documentation.

3.2.2 Design an end-to-end data pipeline to process and serve data for predicting bicycle rental volumes.
Explain the pipeline architecture, including data ingestion, transformation, storage, and serving layers. Discuss scalability, reliability, and monitoring strategies.

3.2.3 Design a scalable ETL pipeline for ingesting heterogeneous data from Skyscanner's partners.
Talk through your approach to handling diverse schemas, ensuring consistency, and optimizing for performance. Mention error handling and data lineage tracking.

3.2.4 Write a query to find all users that were at some point "Excited" and have never been "Bored" with a campaign.
Discuss your use of SQL conditional aggregation or filtering to efficiently scan large event logs and identify qualifying users.

3.2.5 Design a database for a ride-sharing app.
Describe the schema design, normalization, and key tables for tracking rides, users, and transactions. Address scalability and query optimization.

3.3. Dashboarding & Business Communication

Arthur J. Gallagher & Co. values clear, actionable reporting and the ability to communicate complex insights to diverse audiences. Prepare to discuss dashboard design, stakeholder management, and translating analytics into business impact.

3.3.1 Which metrics and visualizations would you prioritize for a CEO-facing dashboard during a major rider acquisition campaign?
Explain how you’d select high-impact metrics, design intuitive visualizations, and ensure the dashboard drives executive decision-making.

3.3.2 Design a dashboard that provides personalized insights, sales forecasts, and inventory recommendations for shop owners based on their transaction history, seasonal trends, and customer behavior.
Discuss personalization strategies, forecasting methods, and how to present recommendations clearly.

3.3.3 How to present complex data insights with clarity and adaptability tailored to a specific audience
Describe your approach to simplifying technical findings, using storytelling, and adjusting content for different stakeholder needs.

3.3.4 Making data-driven insights actionable for those without technical expertise
Emphasize strategies for demystifying analytics, using analogies, and focusing on business outcomes.

3.3.5 Demystifying data for non-technical users through visualization and clear communication
Discuss your use of visual aids, interactive dashboards, and iterative feedback to ensure accessibility.

3.4. User & Customer Insights

Understanding user behavior and customer needs is critical for driving business strategy at Arthur J. Gallagher & Co. Expect questions about segmentation, journey analysis, and designing experiments to uncover actionable insights.

3.4.1 What kind of analysis would you conduct to recommend changes to the UI?
Describe user journey mapping, funnel analysis, and identifying pain points through behavioral data.

3.4.2 How would you determine customer service quality through a chat box?
Explain your approach to sentiment analysis, response time metrics, and customer satisfaction scoring.

3.4.3 Building a model to predict if a driver on Uber will accept a ride request or not
Outline your modeling approach, feature selection, and evaluation metrics.

3.4.4 How would you differentiate between scrapers and real people given a person's browsing history on your site?
Discuss pattern recognition, anomaly detection, and supervised learning for user classification.

3.4.5 How would you explain a scatterplot with diverging clusters displaying Completion Rate vs Video Length for TikTok
Focus on cluster interpretation, key drivers, and communicating actionable recommendations.

3.5 Behavioral Questions

3.5.1 Tell me about a time you used data to make a decision.
Share a specific example where your analysis led to a measurable business outcome. Focus on the problem, your approach, and the impact.

3.5.2 Describe a challenging data project and how you handled it.
Discuss the obstacles you faced, how you prioritized solutions, and what you learned from the experience.

3.5.3 How do you handle unclear requirements or ambiguity?
Explain your method for clarifying objectives, engaging stakeholders, and iterating on solutions.

3.5.4 Tell me about a time when your colleagues didn’t agree with your approach. What did you do to bring them into the conversation and address their concerns?
Highlight your communication skills, openness to feedback, and how you built consensus.

3.5.5 Describe a time you had to negotiate scope creep when two departments kept adding “just one more” request. How did you keep the project on track?
Show your ability to quantify trade-offs, use prioritization frameworks, and maintain transparency with stakeholders.

3.5.6 When leadership demanded a quicker deadline than you felt was realistic, what steps did you take to reset expectations while still showing progress?
Discuss how you communicated risks, adjusted project scope, and delivered incremental value.

3.5.7 Give an example of how you balanced short-term wins with long-term data integrity when pressured to ship a dashboard quickly.
Describe your approach to ensuring reliable results while meeting urgent deadlines.

3.5.8 Tell me about a situation where you had to influence stakeholders without formal authority to adopt a data-driven recommendation.
Share how you built credibility, presented compelling evidence, and navigated organizational dynamics.

3.5.9 Walk us through how you handled conflicting KPI definitions (e.g., “active user”) between two teams and arrived at a single source of truth.
Explain your process for reconciling differences, facilitating discussions, and documenting standards.

3.5.10 Describe how you prioritized backlog items when multiple executives marked their requests as “high priority.”
Show how you applied prioritization frameworks and managed expectations across teams.

4.1 Company-specific tips:

Familiarize yourself with Arthur J. Gallagher & Co.’s core business segments in insurance brokerage, risk management, and consulting. Understand how data-driven decision-making supports their client-centric approach and operational efficiency. Research recent company initiatives, mergers, or innovations in the insurance sector to show your awareness of industry trends and Gallagher’s strategic priorities.

Review Gallagher’s values around ethical practices and collaboration. Prepare examples of how you’ve worked in cross-functional teams and contributed to a culture of transparency and integrity. Demonstrate your ability to communicate complex findings in a way that aligns with the company’s commitment to client service.

Understand the regulatory and compliance landscape in which Gallagher operates. Be ready to discuss how you ensure data privacy, integrity, and compliance in your analytics work, especially when handling sensitive insurance or customer data.

4.2 Role-specific tips:

4.2.1 Practice designing dashboards tailored for executive decision-making and operational reporting. Focus on selecting metrics that matter most to insurance and risk management stakeholders, such as client retention, claims processing efficiency, and portfolio growth. Think about how to present these metrics visually for clarity and impact, using storytelling to guide decision-makers.

4.2.2 Prepare to discuss your experience with data modeling, ETL pipelines, and handling messy datasets. Showcase your ability to design scalable data architectures, clean and validate complex data sources, and optimize pipelines for reliability. Be prepared to walk through a project where you improved data quality or automated a reporting workflow.

4.2.3 Be ready to demonstrate your analytical skills with real-world business scenarios. Expect case questions involving experimental design, A/B testing, and measuring business impact. Practice explaining how you would set up control groups, define KPIs such as customer acquisition cost or churn rate, and interpret results for actionable recommendations.

4.2.4 Highlight your communication strategies for non-technical stakeholders. Prepare examples of how you’ve simplified complex insights for executives or clients, used analogies to demystify analytics, and made recommendations that drove business outcomes. Emphasize your adaptability in tailoring presentations to different audiences.

4.2.5 Show your approach to stakeholder management and requirements gathering. Discuss how you clarify ambiguous requests, prioritize competing demands, and reconcile conflicting definitions of business metrics. Share stories that demonstrate your ability to build consensus and document standards for a single source of truth.

4.2.6 Demonstrate your understanding of business metrics and experimental analysis. Be prepared to analyze user journeys, segment customers, and recommend changes based on behavioral data. Practice discussing how you would evaluate the success of a new product feature or marketing campaign using data-driven methods.

4.2.7 Prepare to discuss how you balance speed with data integrity in fast-paced environments. Share your approach to delivering quick wins without sacrificing long-term reliability—such as shipping dashboards under tight deadlines while maintaining rigorous validation and documentation practices.

4.2.8 Be ready to talk about influencing without authority and driving adoption of BI solutions. Give examples of how you built credibility, presented compelling evidence, and navigated organizational dynamics to get buy-in from stakeholders across departments. Show your ability to champion data-driven change even when you don’t have formal authority.

4.2.9 Brush up on SQL, data visualization tools, and statistical concepts relevant to insurance analytics. Practice writing queries for user segmentation, event tracking, and conditional aggregation. Be ready to discuss your proficiency with tools like Tableau, Power BI, or similar platforms, and your understanding of statistical techniques for retention analysis and forecasting.

4.2.10 Prepare concise, structured stories for behavioral questions. Use the STAR method (Situation, Task, Action, Result) to frame your answers, focusing on how your actions led to measurable business impact. Tailor your stories to highlight adaptability, problem-solving, and your commitment to Gallagher’s mission of client service and innovation.

5.1 How hard is the Arthur J. Gallagher & Co. Business Intelligence interview?
The Arthur J. Gallagher & Co. Business Intelligence interview is challenging but highly rewarding for candidates who excel at both technical analytics and business communication. You’ll face questions that test your ability to build scalable dashboards, analyze complex datasets, and present actionable insights to non-technical stakeholders. The interview also probes your understanding of insurance and risk management metrics, experimental design, and your ability to drive change across cross-functional teams. Candidates who prepare thoroughly for both technical and behavioral rounds, and who can demonstrate a clear link between data work and business impact, stand out.

5.2 How many interview rounds does Arthur J. Gallagher & Co. have for Business Intelligence?
Typically, there are five to six rounds: an initial application and resume review, a recruiter screen, one or two technical/case interviews, a behavioral interview, and a final onsite round with BI leadership and cross-functional partners. Some candidates may also participate in a technical presentation or deep dive into a past project during the final stage.

5.3 Does Arthur J. Gallagher & Co. ask for take-home assignments for Business Intelligence?
Take-home assignments are occasionally part of the process, especially for roles requiring advanced dashboarding or data modeling. These assignments usually involve designing a dashboard, analyzing a dataset, or preparing a short presentation on business metrics relevant to insurance or risk management. The goal is to assess your practical skills and your ability to communicate findings to a business audience.

5.4 What skills are required for the Arthur J. Gallagher & Co. Business Intelligence?
Key skills include advanced data analysis, dashboard development, SQL proficiency, data modeling, ETL pipeline design, and business communication. Experience with data visualization tools (such as Tableau or Power BI), experimental design, and translating complex findings for non-technical stakeholders is highly valued. Familiarity with insurance, risk management, and compliance requirements will set you apart.

5.5 How long does the Arthur J. Gallagher & Co. Business Intelligence hiring process take?
The process typically takes 3-5 weeks from initial application to final offer. Fast-track candidates may complete the process in as little as 2-3 weeks, but most applicants can expect about a week between each stage, with some variation depending on team availability and candidate scheduling.

5.6 What types of questions are asked in the Arthur J. Gallagher & Co. Business Intelligence interview?
Expect a mix of technical, case-based, and behavioral questions. Technical questions cover data analysis, dashboard design, data quality, ETL pipelines, and business metrics. Case questions may involve designing experiments, analyzing customer journeys, or recommending changes based on operational data. Behavioral questions focus on communication, stakeholder management, conflict resolution, and adaptability in fast-paced environments.

5.7 Does Arthur J. Gallagher & Co. give feedback after the Business Intelligence interview?
Arthur J. Gallagher & Co. typically provides high-level feedback through recruiters, especially regarding overall fit and strengths. Detailed technical feedback may be limited, but candidates are encouraged to ask for clarification on areas for improvement.

5.8 What is the acceptance rate for Arthur J. Gallagher & Co. Business Intelligence applicants?
While specific rates aren’t published, the Business Intelligence role is competitive given the company’s global reputation and the strategic impact of the position. Industry estimates suggest an acceptance rate of 3-7% for well-qualified applicants.

5.9 Does Arthur J. Gallagher & Co. hire remote Business Intelligence positions?
Yes, Arthur J. Gallagher & Co. offers remote opportunities for Business Intelligence professionals, with some roles requiring occasional travel or in-person collaboration depending on team needs and project scope. The company values flexibility and supports remote work arrangements for qualified candidates.

• Related guides:
  • Arthur J. Gallagher & Co. interview questions
  • Business Intelligence interview guide
  • Top Business Intelligence interview tips

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