Technical practice
How would you build a forecasting strategy and roadmap across product groups?
What to coverSuggested preparation: Explain how you would connect forecasting objectives to business goals, prioritize product groups, and define stages for implementation and scale. Address dependencies, decision points, and how you would adapt the roadmap as needs change.
How would you select and evaluate forecasting approaches?
What to coverSuggested preparation: Compare suitable baselines and ML approaches using time-based validation and measures tied to the business objective. Discuss the trade-off between accuracy, interpretability, maintenance effort, and performance across product groups.
How would you make a forecasting approach scalable across product groups?
What to coverSuggested preparation: Describe which data definitions, evaluation practices, and model processes you would standardize, and where product-group differences may require flexibility. Explain how you would check that a shared approach remains useful as it expands.
How would you assess whether data is ready for forecasting?
What to coverSuggested preparation: Cover availability, completeness, consistency, timeliness, and changes in source data. Explain how you would investigate gaps with data owners and decide whether to improve the data, adjust the approach, or delay a forecast.
Which KPIs would you use to assess predictive analytics performance and impact?
What to coverSuggested preparation: Distinguish model-performance measures from measures of business use and impact, and explain how you would establish a baseline. Discuss how regional leaders could use scorecards without obscuring important differences between groups.
What process would you establish to improve forecasting models over time?
What to coverSuggested preparation: Explain how you would review forecast errors, gather stakeholder feedback, and detect changes in data or business needs. Describe criteria for updating a model and how you would verify that an update helps before wider use.
How would you choose a technology stack with IT for ML and forecasting work?
What to coverSuggested preparation: Discuss requirements you would clarify before choosing components in an Azure or AWS data-cloud environment. Weigh integration, data access, maintainability, and the team's ability to operate the approach; the posting does not specify particular services.
How would you use data transformation and queries to support reliable forecasts?
What to coverSuggested preparation: Explain how you would create consistent, traceable inputs from source data and validate transformations and query results. Address how incorrect joins, changing definitions, or delayed data could affect forecasts.
How would you put fairness, transparency, and accountability into forecasting practice?
What to coverSuggested preparation: Describe checks for uneven outcomes across relevant groups, ways to communicate assumptions and limitations, and clear ownership of review decisions. Acknowledge that the appropriate checks depend on how forecasts are used.
How would you turn regional scorecards into decisions about forecasting solutions?
What to coverSuggested preparation: Explain how you would agree on comparable KPI definitions with regional leaders while allowing for meaningful local differences. Discuss how you would interpret conflicting results and decide what to change or investigate.
Behavioural practice
Tell me about a time you led a team across geographies toward a shared deadline.
What to coverSuggested preparation: Use a real situation, the actions you took to clarify work items and ways of working, and the result. Include how you handled coordination across locations and cultures.
Describe a time you aligned IT and business stakeholders on an unclear analytics project.
What to coverSuggested preparation: Set out the conflicting or incomplete needs, how you clarified scope and influenced a decision, and what resulted. Focus on your communication and diplomacy rather than assuming agreement was immediate.
Tell me about a time you turned an ambiguous strategy into action while managing competing priorities.
What to coverSuggested preparation: Explain the situation, how you set direction and made trade-offs, and the result. Make clear what you deferred or revisited as information changed.
Describe a time you led others through root-cause analysis of an analytics problem.
What to coverSuggested preparation: Give a real example of the problem, how you helped the team test possible causes, and the resulting corrective action. Distinguish the underlying cause from the initial symptom.
Tell me about a process improvement you led using Scrum or Lean thinking.
What to coverSuggested preparation: Describe the original workflow, the change you led, and the result using evidence you actually have. Explain how you involved the team and checked whether the improvement lasted.