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The use case was a dumb one: forecasting of the future operations, in the retail bank application, with the very same accuracy as the historical operations (for instance, the application should forecast that you will buy some cake at Albert Heijn in ten days from now, on a Tuesday morning at 10:12, for an amount of 1.27 Euros). When I tried to transform the use case so that it makes more sense business-wise (for instance, a budget planning exercise, where we still keep the analysis of time series), the interviews were dumb and wanted to stick to the original formulation of the use case.
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Chapter Lead Data Analytics

Interviewed at ING

4.1★
Feb 23, 2018

The use case was a dumb one: forecasting of the future operations, in the retail bank application, with the very same accuracy as the historical operations (for instance, the application should forecast that you will buy some cake at Albert Heijn in ten days from now, on a Tuesday morning at 10:12, for an amount of 1.27 Euros). When I tried to transform the use case so that it makes more sense business-wise (for instance, a budget planning exercise, where we still keep the analysis of time series), the interviews were dumb and wanted to stick to the original formulation of the use case.

Round 1: 1) Duplicates in an array in O(n) time and O(1) space. 2) Left-view of a binary tree. 3) Kafka producer-consumer lag. 4) Convert list to map using streams. and others I dont remember, but they were on basic concepts. Round 2: 1) kafka working and architecture. 2) Design patterns as above. and some other basic questions.
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Technical Lead

Interviewed at adidas

3.9★
Jun 27, 2022

Round 1: 1) Duplicates in an array in O(n) time and O(1) space. 2) Left-view of a binary tree. 3) Kafka producer-consumer lag. 4) Convert list to map using streams. and others I dont remember, but they were on basic concepts. Round 2: 1) kafka working and architecture. 2) Design patterns as above. and some other basic questions.

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