Marsh McLennan Interview Experience - Full Recruitment Process
Sharing my experience of the Marsh McLennan recruitment process. The process was divided into different levels, and the overall evaluation was based on performance across the assessment stages followed by the interview.
Candidate Profile
Education: BE from a Tier 1 college
Years of Experience: 0.5 years of Internship experience
Prior Experience: Data Scientist intern at a product-based Startup
Prior Compensation: ~₹7.6 LPA
Offer Details
Date of Offer: July 2025
Company: Marsh McLennan
Title: Engineer – Native AI
Location: Mumbai, India
Total CTC: ~₹13.66 LPA/year, including fixed and variable components.
Approximate Compensation Breakdown
| Component | Monthly (₹) | Annual (₹) |
|---|---|---|
| Basic | ₹45,533 | ₹5.46L |
| HRA | ₹22,767 | ₹2.73L |
| Flexi Benefits | ₹33,286 | ₹3.99L |
| Performance Incentive | ₹11,383 | ₹1.37L |
| Employer PF Contribution | ₹864 | ₹0.10L |
| Total CTC | ₹1,13,833 | ₹13.66L |
The compensation numbers are approximate and rounded, so the monthly figures may not exactly multiply to the annual figures because of rounding.
Recruitment Process
The process started with Level 1, which was an online MCQ-based assessment. The questions covered general aptitude as well as technical fundamentals. The technical portion mainly focused on areas such as programming fundamentals, OOPs, DBMS, SQL, operating systems, computer networks and basic problem-solving. The difficulty was not extremely high, but having a good understanding of the fundamentals was important because the assessment was time-bound.
After Level 1, shortlisted candidates moved to Level 2, which was a more practical, coding-oriented round. This round was based around full-stack development and required candidates to actually work on coding problems rather than simply selecting answers. The exact technology stack could vary depending on the role, but preparation around frontend concepts, backend/API development, databases, programming fundamentals and basic DSA was useful. Candidates were expected to understand the code they were writing and be able to reason about their approach.
After Level 2, there was a separate Level 2.1 stage for candidates who had faced an issue during Level 2. Level 2.1 was not mandatory for everyone. Only candidates who had some problem, technical issue or difficulty during the original Level 2 assessment were required to take Level 2.1.
Candidates who completed Level 2 successfully and did not need Level 2.1 were not required to take the additional assessment. In their case, the Level 2 score itself was considered for the subsequent evaluation. For candidates who were required to appear for Level 2.1, the additional assessment was considered as part of their evaluation.
This made Level 2.1 more of a continuation or replacement opportunity for candidates who had an issue during Level 2, rather than a completely separate compulsory round for everyone.
After the assessment stages, candidates who cleared the required criteria proceeded to the interview round. The interview was more focused on understanding the candidate rather than simply checking whether they could solve an assessment question. A significant portion of the discussion could revolve around the candidate's resume, projects, technologies mentioned on the resume, programming fundamentals and the candidate's understanding of the work they had done.
For the technical portion of the interview, I would recommend being comfortable with OOP concepts, DBMS, SQL, DSA and the programming language mentioned on the resume. Questions can move from basic conceptual questions to asking the candidate to write or explain a solution. The interviewer may ask about inheritance, polymorphism, abstraction, interfaces, collections, exception handling or the difference between different OOP concepts. SQL questions can involve joins, grouping, subqueries, aggregate functions, normalization, indexes and transactions.
The project discussion can also become quite detailed. If React, Java, Python, Node.js, SQL or any other technology is mentioned on the resume, it is important to actually understand how it was used in the project. Questions can include why a particular technology was selected, how the frontend communicates with the backend, how the database is designed, how APIs work, what challenges were encountered and what could be improved in the project.
The coding portion of the interview can involve relatively straightforward DSA problems involving arrays, strings, hashing, searching, sorting, linked lists or similar topics. The interviewer may also be interested in the candidate's thought process rather than only the final code, so explaining the brute-force approach, optimized approach and time and space complexity is useful.
The final part of the discussion can include HR or behavioural questions such as why Marsh McLennan, an introduction about yourself, strengths and weaknesses, project challenges, teamwork, handling deadlines and career goals.
Overall, the process was not just about solving DSA questions. The assessment stages tested technical fundamentals and practical coding ability, while the interview focused more on whether the candidate actually understood their fundamentals, projects and technologies.
The important distinction in the process was between Level 2 and Level 2.1. Level 2.1 was only applicable to candidates who had faced a problem during Level 2. Candidates who completed Level 2 without any such issue did not need to take Level 2.1, and their original Level 2 score was used for the evaluation.
For preparation, I would therefore focus less on memorising random interview questions and more on being genuinely comfortable with programming fundamentals, OOPs, SQL/DBMS, basic DSA, full-stack concepts and everything written on the resume. The interview becomes significantly easier when you can confidently explain the reasoning behind your code, your projects and the technical decisions you made.