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A.P. Moller - Maersk Interview Questions

A/B Testing

Algorithms

Analytics

Machine Learning

Probability

Product Metrics

Python

Statistics

A.P. Moller - Maersk Interview Guides

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

Company DescriptionA.P. Moller - Maersk is a leading integrated transport and logistics company dedicated to connecting the world and enabling global trade. With a mission to help individuals and businesses grow and thrive, Maersk operates in 130 countries with a workforce of approximately 110,000 employees. The company is committed to innovation and sustainability, delivering value-driven solutions for its customers and society. Role DescriptionLocation: Bangalore (Hybrid)Experience:- Junior Level: 4+ years- Senior Level: 8+ years This full-time role as a Data Scientist located in Bengaluru. We are seeking talented and driven Data Scientists to join our growing team. Whether you're early in your career or bring years of experience, we value deep technical expertise and a strong problem-solving mindset. You’ll work on impactful projects involving Classical Machine Learning or Generative AI.Candidates should demonstrate in-depth understanding of model architectures, and while specialization in either Classical ML or Generative AI is expected, a working knowledge of both is required. Key Responsibilities<ul><li>Develop, evaluate, and deploy ML/AI models for forecasting and predictive analytics.</li><li>Own end-to-end model lifecycle: from data exploration and feature engineering to deployment and monitoring.</li><li>Collaborate with product, engineering, and business teams to translate requirements into scalable data science solutions.</li><li>Conduct architectural deep-dives and contribute to technical design discussions.</li><li>Stay current with advancements in ML/AI and proactively apply them to solve business problems.</li><li>(For senior roles) Mentor junior team members and lead technical initiatives.</li></ul> Qualifications<ul><li>Master's or Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field.</li><li>Proficiency in Data Science techniques, including predictive modeling and machine learning applications</li><li>Strong knowledge of Statistics and Data Analytics for interpreting and analyzing key datasets</li><li>Prior experience as a Data Scientist in a professional setting.</li><li>Strong expertise in either Classical ML or Generative AI:</li></ul><ol><li>Classical ML: Regression, Classification, Ensemble Methods, Time Series Forecasting, etc.</li><li>Generative AI: Transformers, Diffusion Models, LLMs, GANs, VAEs, Agentic AI, RAG etc.</li></ol><ul><li>Solid understanding of underlying architectures and mathematical foundations of ML/AI models.</li><li>Hands-on experience with forecasting techniques (e.g., ARIMA, Prophet, RNNs).</li><li>Proficiency in Python and ML libraries (e.g., scikit-learn, PyTorch, TensorFlow).</li><li>Ability to explain and discuss core concepts across both Classical ML and Generative AI domains</li><li>Familiarity with at least one cloud platform (AWS, Azure, GCP).</li><li>Ability to work collaboratively in cross-functional teams and apply problem-solving skills to complex business needs</li><li>Strong programming skills in languages such as Python, R, or similar, are highly desirable</li></ul> Bonus Points for<ul><li>Experience building and deploying large-scale ML/AI applications in production.</li><li>Cloud-native development experience (e.g., using cloud services for training, deployment, monitoring).</li></ul> What We Offer<ul><li>Opportunity to work on cutting-edge AI/ML problems with real-world impact.</li><li>A collaborative, intellectually stimulating environment.</li><li> Competitive compensation and flexible work arrangements.</li><li>Continuous learning and growth opportunities.</li></ul>

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

A.P. Moller - Maersk Interview Questions

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A.P. Moller - Maersk Interview Questions

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