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The phone interview was generally non-technical. The 2nd takehome exercise task was to write a script that processes a CSV file of customer transactions, keeps a running mean and standard deviation of transactions by customer ID, observes large deviations of individual transaction amounts from the running mean and, when such deviations are observed, generates alerts. This was to be done by implementing just one method, for which they had written a header definition. The instructions stated certain requirements: scalability, readability and code structure, logging and testing, and how simple it is to run and evaluate the code. Observe that some of these involve a large element of subjectivity. There was no mention of persistence, or function naming conventions.
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Machine Learning Engineer

Interviewed at Featurespace

4.3★
Mar 11, 2020

The phone interview was generally non-technical. The 2nd takehome exercise task was to write a script that processes a CSV file of customer transactions, keeps a running mean and standard deviation of transactions by customer ID, observes large deviations of individual transaction amounts from the running mean and, when such deviations are observed, generates alerts. This was to be done by implementing just one method, for which they had written a header definition. The instructions stated certain requirements: scalability, readability and code structure, logging and testing, and how simple it is to run and evaluate the code. Observe that some of these involve a large element of subjectivity. There was no mention of persistence, or function naming conventions.

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