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First round: * Experience and why you left jobs? * Why General Mills? * Explain PCA to a jr.DS * Tell me about a time that you had conflict with your manager? * Tell me about a time when you worked with other teams to get your job done? * How do you explain coefficients of a linear regression to a business person? * Tell me about a time you had to convince your manager to listen to you? * What are your long term career plans? Codility: * Implement Mutual Info probability distribution using Python Final round: Hiring Manager: * How do you deal with bad data? How did you handle them ? * How do deal with missing values ? * Is more data always good ? * What is cross-validation, explain ? * Which tool do you prefer ? R or Python ? * What do you do when distribution of train & test data is different ? * What is the size of data that you worked with? No of observations and No of features ? * Your experience writing production level code ? * experience with GCP ? * Around Betty crocker's website. Recipe recommendations? How do you ask them questions ? How do you see if your model is performing well or not ? How do you deploy a model ? * How to motivate team members ? * How did you help under performers 2 Sr. DS: provides a python notebook, which is almost same as https://github.com/andreagrandi/ml-pima-notebook/blob/master/PimaIndiansDiabetes.ipynb data team manager: 1 question per General Mills values, around helping team members, a situation where you did the right thing, etc
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Senior Data Scientist

Interviewed at General Mills

4★
Jun 10, 2021

First round: * Experience and why you left jobs? * Why General Mills? * Explain PCA to a jr.DS * Tell me about a time that you had conflict with your manager? * Tell me about a time when you worked with other teams to get your job done? * How do you explain coefficients of a linear regression to a business person? * Tell me about a time you had to convince your manager to listen to you? * What are your long term career plans? Codility: * Implement Mutual Info probability distribution using Python Final round: Hiring Manager: * How do you deal with bad data? How did you handle them ? * How do deal with missing values ? * Is more data always good ? * What is cross-validation, explain ? * Which tool do you prefer ? R or Python ? * What do you do when distribution of train & test data is different ? * What is the size of data that you worked with? No of observations and No of features ? * Your experience writing production level code ? * experience with GCP ? * Around Betty crocker's website. Recipe recommendations? How do you ask them questions ? How do you see if your model is performing well or not ? How do you deploy a model ? * How to motivate team members ? * How did you help under performers 2 Sr. DS: provides a python notebook, which is almost same as https://github.com/andreagrandi/ml-pima-notebook/blob/master/PimaIndiansDiabetes.ipynb data team manager: 1 question per General Mills values, around helping team members, a situation where you did the right thing, etc

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