They asked very specific questions on ML algorithms (eg, give me the three drawbacks of the PCA algorithm), without being interested in my capacity to see the bigger picture (for instance, how to put PCA in the perspective of dimensionality reduction, and how it compares to other algorithms for that purpose).
Why Nestle
Asked mostly behavioral questions like how I'd cope with deadlines and work with other teams, some simple technical questions like how long I need to sort and retrieve files.
All skills actually needed for data analytics aside, do you already know how to work with our financial products so we can get spurious analyses that are based on our existing preconceptions?
Why Golin? Why analytics? Do you have experience using data to solve a problem?
How would you design a data model for this
Case study: Some data given on warehouse and the location of warehouse was to be decided.
Sales force sizing problem
The most difficult phase of the interview was the unstructured case study where in a lot of analysis was expected within very less time.
Past project-related discussion Case study on lending use cases.
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