Excel - sumifs, rank, lookup, pivot, slicer, match, index SQL - queries on joins, rank, partition, group, order, having clause etc Data Analytics - Modelling techniques, steps, model validation, types of models etc Power BI - Aggregations, modelling, slicers, sorting, filtering Case study - Expense/Cost optimization General - Past experience, data management, data cleansing, ETL, retail concepts, finance concepts
Typical Q's about aspirations, past experiences. Some business problems also proposed during the interview.
Technical interview: Explain confusion matrix and metrics derived from it. Explain SQL cross join. Product/Business interview: Provides a dashboard with 8 KPIs and asks for 3 key insights.
- Tell us about yourself - How do you account for external variables that may not be included in the dataset
how do you handle with a difficult stakeholder
What is your favorite nestle project
Technical questions covered SQL, data analysis, R and some ML concepts.
Tell me about your skill set and how do you think it can be a great fit for this role?
What do you think could be our KEY KPIs?
Have you worked with Python, SQL, or R for at least 5 years?
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