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Marsh & Mclennan Companies Interview Questions

A/B Testing

Algorithms

Analytics

Machine Learning

Probability

Product Metrics

Python

Statistics

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Suppose there exists a new airline named Jetco that flies domestically across North America. Jetco recently had a study commissioned that tested the boarding time of every airline, and it came out that Jetco had the fastest average boarding times of any airline.

What factors could have biased this result, and what would you look into?

What could potentially bias the average boarding time in favor of an airline that only flies domestically?

What could potentially bias the average boarding time in favor of an airline that only flies domestically?

Boarding Times Bias

A new airline came out as the fastest average boarding times compared to other airlines.  What factors could have biased this result and what would you look into?

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

What is a key disadvantage of the F-test when compared to multiple t-tests?

What is a key disadvantage of the F-test when compared to multiple t-tests?

Hundreds of Hypotheses

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

In an A/B test, how can you check if assignment to the various buckets was truly random?

In an A/B test, which of the following is a common method to determine if the assignment to the test groups was truly random?

In an A/B test, which of the following is a common method to determine if the assignment to the test groups was truly random?

Random Bucketing

A/B Testing & Experimentation

We are seeking a talented individual to join our Mercer Direct Investment/SECOR team at Mercer.. This role will be based in New Yor City and offers a hybrid work arrangement, requiring a minimum of three days per week in the office. As a Front Office Trading Technology & Data Analyst, you will play a key role in supporting the entire trade lifecycle, from order staging to post-trade analysis, while providing insights to optimize trading strategies. Youll lead the design of trading workflows across multiple asset classes, collaborating with traders and portfolio managers to enhance platforms and processes. Developing APIs and microservices, ensuring data accuracy, and resolving data discrepancies will be central to maintaining operational efficiency. This role offers the opportunity to drive technological and data quality improvements in a dynamic trading environment! <h5>We will count on you to: </h5> <ul><li>Help lead the design and implementation of trading workflows across multiple asset classes, integrating order staging, execution, and booking processes </li><li>Collaborate with portfolio managers and traders to gather requirements and deliver enhancements to order management and execution management platforms </li><li>Develop and maintain APIs and microservices to support real?time trade execution and post?trade processing </li><li>Implement data quality checks and validation rules to ensure accuracy and consistency of financial data </li><li>Collaborate with front and middle office teams to address data discrepancies quickly </li><li>Act as the primary point of contact for data quality issues between front and middle office teams. </li><li>Maintain documentation of data quality checks and escalation procedures </li><li>Conduct root cause analysis for data issues and implement long?term solutions </li><li>Drive improvements in data quality processes and standards </li> </ul><h5>What you need to have: </h5><ul><li>Bachelors degree in Engineering, Statistics, Mathematics or Computer Science preferred </li><li>2+ years of experience with financial products and trading systems </li><li>Experience with modern web frameworks and libraries (e.g., FastAPI, Flask, React, MUI) </li><li>Strong coding capability in Python </li><li>Solid understanding of SQL </li><li>Proven ability to work across the full software development lifecycle in a fast?paced, collaborative environment </li><li>Strong communication and problem?solving skills </li> </ul><h5>Why join our team: </h5><ul><li>We help you be your best through professional development opportunities, interesting work and supportive leaders. </li><li>We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have an impact on colleagues, clients, and communities. </li><li>Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being. </li> </ul>Mercer, a business of Marsh McLennan (NYSE: MMC), is a global leader in helping clients realize their investment objectives, shape the future of work and enhance health and retirement outcomes for their people. Marsh McLennan is a global leader in risk, strategy and people, advising clients in 130 countries across four businesses: Marsh, Guy Carpenter, Mercer and Oliver Wyman. With annual revenue of $24 billion and more than 90,000 colleagues, Marsh McLennan helps build the confidence to thrive through the power of perspective. For more information, visit mercer.com, or follow on LinkedIn and X. Marsh McLennan is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age background, disability, ethnic origin, family duties, gender orientation or expression, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, veteran status (including protected veterans), or any other characteristic protected by applicable law. If you have a need that requires accommodation, please let us know by contacting reasonableaccommodations@mmc.com. Marsh McLennan is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh McLennan colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one anchor day per week on which their full team will be together in person. #J-18808-Ljbffr

Question	Topic	Difficulty	Ask Chance
Boarding Times Bias	Statistics	Medium	Very High
Hundreds of Hypotheses	Statistics	Medium	Very High
Random Bucketing	A/B Testing & Experimentation	Medium	Very High

Marsh & Mclennan Companies Interview Questions

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Marsh & Mclennan Companies Interview Questions

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