Whenever you're ready, walk me through how you'd approach this.
You're in the middle of a data science project when a meaningful problem appears, such as missing data, a model underperforming, or a dependency slipping. You need to respond quickly without losing sight of the business goal or creating confusion across the team.
How do you approach a problem encountered in a project?