Preparing for an interview at Marsh & McLennan requires a balanced approach to technical preparation and behavioral storytelling. You must demonstrate that you are not only comfortable working with large datasets but also highly capable of collaborating with cross-functional teams.

Role-Related Knowledge – You must have a strong grasp of data analysis tools and basic HR metrics. Be prepared to discuss compensation structures, performance management metrics, and talent acquisition data. Interviewers will evaluate your technical proficiency through practical tests and scenario-based questions.

Problem-Solving Ability – Marsh & McLennan values candidates who can approach ambiguous data challenges systematically. You should be able to break down a complex business problem, formulate hypotheses, outline your analytical methodology, and explain how you would validate your findings.

Communication & Stakeholder Management – As a People Analytics Specialist, you will act as an advisor to HR business partners and business leaders. Interviewers will assess your ability to translate statistical concepts into plain business language and build trust with stakeholders.

Culture Fit & Alignment – The firm places a high priority on professional integrity, collaboration, and respect for client and employee data privacy. You should demonstrate a strong understanding of Marsh & McLennan's global footprint and show how your personal values align with their culture of inclusion and excellence.

The interview process for the People Analytics Specialist role at Marsh & McLennan is thorough and designed to evaluate both your technical execution and your behavioral fit. While the exact steps can vary slightly by region and seniority level, the overall flow remains consistent across most global locations.

Typically, the process begins with an asynchronous digital assessment and progresses through multiple rounds of conversations with HR, hiring managers, and senior business leaders. Candidates should expect a mix of structured technical case studies and deep-dive behavioral interviews over a multi-week period.

This visual timeline illustrates the typical progression from your initial application to the final offer stage. Candidates should use this roadmap to pace their preparation, ensuring they focus on technical Excel skills early in the process and transition to advanced behavioral preparation for the later rounds.

To stand out during the selection process, you must excel in three core evaluation areas that the hiring team focuses on most.

Excel & Data Manipulation

Excel remains a primary tool for day-to-day data tasks in this role. You will likely face a timed, hands-on Excel assessment designed to test your efficiency and accuracy under pressure.

Be ready to go over:

• Data Cleaning – Using text-to-columns, removing duplicates, and handling blank or erroneous cells within a workforce dataset.
• Conditional Logic & Aggregation – Utilizing formulas such as SUMIF, COUNTIF, and AVERAGEIF to summarize headcount and payroll data.
• Data Retrieval – Implementing VLOOKUP, XLOOKUP, or INDEX/MATCH to merge candidate or employee records from disparate sources.
• Advanced concepts (less common) – Creating dynamic Pivot Tables, writing basic VBA macros, or building nested logical statements to automate standard HR reporting templates.

Example scenarios:

• "You are given a raw spreadsheet of 10,000 global employees. Use conditional formulas to calculate the average salary of employees in a specific region who have a performance rating of 'Exceeds Expectations'."
• "Identify and resolve discrepancies between two separate employee rosters using lookup functions, then summarize your findings in a clean executive summary."

Statistical Reasoning & Domain Knowledge

Beyond manipulating data, you must understand the underlying statistical concepts that govern compensation and talent metrics.

Be ready to go over:

• Descriptive Statistics – Explaining and calculating mean, median, mode, variance, and standard deviation in the context of salary distributions.
• Distribution Analysis – Understanding percentiles, quartiles, and how outliers can skew average compensation figures.
• Compensation Metrics – Discussing terms like market pricing, salary bands, compa-ratios, and geographic differentials.

Example scenarios:

• "Explain why a median salary might be a more reliable metric than a mean salary when analyzing pay equity across a newly acquired business unit."
• "A hiring manager wants to offer a candidate a salary at the 75th percentile of our current pay band. Walk me through how you would calculate this value and explain the financial implications to the manager."

Case Study & Behavioral Fit

The final stages of the interview process focus heavily on how you apply your skills to real-world business challenges and how well you collaborate with others.

Be ready to go over:

• Structured Problem Solving – Approaching open-ended business cases systematically and explaining your rationale clearly.
• Stakeholder Communication – Presenting data insights to non-technical audiences and handling pushback from business leaders.
• STAR Method Delivery – Structuring your behavioral answers using the Situation, Task, Action, and Result framework to showcase your impact.

Example scenarios:

• "An executive notices a sudden spike in voluntary turnover within the technology division. Walk me through how you would design an analytical study to investigate the root causes of this attrition."
• "Describe a time when you had to deliver bad news or unexpected analytical results to a senior stakeholder who was expecting a different outcome."

As a People Analytics Specialist at Marsh & McLennan, your day-to-day work will revolve around maintaining data integrity, generating actionable insights, and supporting strategic talent initiatives. You will work closely with HR business partners, compensation specialists, and business unit leaders to ensure that the firm's talent decisions are backed by robust data.

A significant portion of your responsibilities will involve designing, building, and maintaining standard reports and interactive dashboards. These tools allow HR leaders to monitor key metrics such as headcount growth, turnover rates, diversity demographics, and compensation competitiveness in real time.

Additionally, you will participate in ad-hoc analytical projects. For example, during annual compensation planning cycles, you will help model salary increase budgets, analyze market benchmark data, and identify pay anomalies. Your ability to collaborate effectively with global, cross-functional teams will be essential, as you will regularly pull data from centralized systems like Workday and translate it for localized business needs.