Technical practice
How would you turn a complex business challenge into a data science problem?
What to coverExplain how you would define the target, establish a baseline, and choose measures of success that reflect the project objective. Suggested preparation: discuss trade-offs between model performance and the needs of the application.
How would you preprocess a large dataset for an AI application?
What to coverCover data quality, missing values, inconsistent records, and how you would make preprocessing repeatable. Suggested preparation: explain how dataset size affects your choice of processing approach.
How would you design and evaluate features for a machine learning model?
What to coverDescribe how you would select or construct useful features and test whether they improve results. Suggested preparation: address data leakage and whether the same features will be available when the model is used.
How would you choose a machine learning framework for a scalable model?
What to coverCompare options against the model’s needs, dataset size, deployment environment, and team maintainability rather than naming a preferred library alone. Suggested preparation: explain a trade-off you would verify through a small implementation.
How would you structure Python or R code for an AI application?
What to coverDescribe how you would separate data preparation, model logic, and application integration. Suggested preparation: discuss tests and reproducibility as ways to support the posting’s production-ready quality requirement.
When would you use a deep learning or neural network approach?
What to coverExplain what properties of the problem might justify it over a simpler model and how you would evaluate the difference. The posting lists these techniques as possible solution components, so prepare to discuss selection rather than assume every project needs them.
How would you incorporate a generative AI model into a solution?
What to coverDescribe the model’s intended role, how you would evaluate its outputs, and how it would connect to the wider application. Suggested preparation: address reliability and the trade-off between model capability and operational constraints.
If a solution needed image processing, how would you approach it?
What to coverExplain how you would define the image-processing task, prepare suitable data, and assess output quality. This is a suggested scenario based on an optional capability in the posting, not a stated project.
How would you choose between cloud and on-premises application pipelines?
What to coverCompare deployment needs, integration, scalability, and operational constraints while keeping the application production-ready. Suggested preparation: explain which assumptions you would confirm before making the choice.
How would you diagnose an AI application that performs well in development but poorly after deployment?
What to coverWalk through checks on input data, preprocessing, model outputs, and the application pipeline to isolate the problem. Suggested preparation: discuss what evidence would distinguish a model issue from an integration issue.
Behavioural practice
Tell me about a team decision you led on an AI or machine learning solution.
What to coverUse a real situation, your decision-making actions, and the result. Explain how you weighed technical options and took responsibility for the team’s choice.
Describe a problem you helped solve across multiple teams.
What to coverGive the situation, what you did to coordinate the teams, and the result. Focus on how you resolved differing views or dependencies without overstating your individual role.
Tell me about a time you mentored a junior colleague.
What to coverDescribe the skill-development need, the support you provided, and the observable result. Choose a real example that shows how you adapted your approach to the colleague.
Describe how you kept an AI initiative aligned with a project objective.
What to coverSet out the situation, how you worked with other functions to clarify priorities, and the result. Explain any trade-off you had to communicate.
Tell me about leading the delivery of a solution to a complex business challenge.
What to coverUse a real situation, your actions in guiding the design or implementation, and the result. Distinguish your contribution from the team’s and explain how you assessed whether the solution addressed the challenge.