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Microsoft Data Scientist Mock Interview

To help you prepare for a Data Scientist interview at Microsoft, here are 30 interview questions and answer examples.

Microsoft was written by and updated on October 25th, 2021. Learn more here.

Question 1 of 30

Here at Microsoft, we use several programming languages to create our software. What programming languages do you have experience using? Of these, which do you have the most experience with? Which do you have the least experience with?

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List of Microsoft Data Scientist Interview Questions & Answers

  1. 1.

    Here at Microsoft, we use several programming languages to create our software. What programming languages do you have experience using? Of these, which do you have the most experience with? Which do you have the least experience with?

  2. 2.

    What data visualization tools do you have experience using? Which one is your favorite to use and why?

  3. 3.

    Do you follow the hypothesis that many small decision trees are more accurate than one large one?

  4. 4.

    In your past positions, have you had experience contributing to the improvement of data analysis processes, database management, data infrastructure, or anything along those lines? If so, please explain your contributions.

  5. 5.

    Describe to me a data project you worked on in the past that you would do differently with the knowledge/experience you have acquired up to this point and/or new technology that was not available at the original time of the project.

  6. 6.

    In your opinion, is mean square error a good or bad measure of model performance?

  7. 7.

    Can you describe some of the steps you take to ensure that a regression model fits the data?

  8. 8.

    Describe a time when you had to present findings to a non-technical audience (very little or no background in data or databases). What strategies did you use to ensure the audience did not get confused and clearly understood the message?

  9. 9.

    Data Scientists do a lot of exploring and testing of hypotheses. Tell me about a time where you were given freedom to explore a business problem with very few parameters. What was your initial approach in attacking this project?

  10. 10.

    What statistical software programs do you have experience using in past positions in this field? Which one do have you the most experience with or feel the most confident using?

  11. 11.

    Data visualization is an important skill that will be used often here at Microsoft when communicating results with stakeholders. Describe to me one of your most innovative data visualization ideas that went beyond pie and bar charts.

  12. 12.

    To be a successful Data Scientist, many in the industry believe it is important to keep up-to-date on the newest technologies and methodologies. What new data-related technology/methodology have you heard of that you wish you could learn more about?

  13. 13.

    Many companies rely on Data Scientists to tell them what analysis is possible with the data available. Talk about a time when you took the initiative to recommend a new business measure for the company to track.

  14. 14.

    Can you describe how Data Analysis is used by businesses and other organizations like Microsoft?

  15. 15.

    The work of a Data Scientist can have a large impact on the success of Microsoft's business. Is there a time you felt your work as a Data Scientist impacted your company's strategy development? Explain your role and contribution.

  16. 16.

    When your job requires you to be immersed in data, you can discover some interesting patterns or trends. What is the most interesting learning you discovered through the mining/exploration of data?

  17. 17.

    Microsoft is in the process of implementing machine learning in our applications. Describe to me your experience with machine learning methods. Is there a particular method you have more experience with than others?

  18. 18.

    What experience do you have conducting text analytics? Describe a project you worked on that required text analytics.

  19. 19.

    How have past positions, unrelated to data analysis, helped you in your current profession as a Data Scientist? How will this help you to be successful here at Microsoft?

  20. 20.

    Describe a project where you had a surprisingly difficult time dealing with unstructured data. How did you overcome the obstacles and what tools did you use?

  21. 21.

    Here at Microsoft, we use several programming languages to create our software. Can you compare SAS, R, and Python programming tools and describe their use in Data Analytics?

  22. 22.

    A a Data Scientist, how do you employ statistics to analyze data and develop business recommendations?

  23. 23.

    What is Data Cleansing and why is it important in Data Analysis?

  24. 24.

    What is a decision tree, and how would you use this in your job as a data scientist here at Microsoft?

  25. 25.

    What are some of the assumptions required to accurately perform a linear regression analysis?

  26. 26.

    Do you perform data wrangling and data cleaning before applying machine learning algorithms to your data analysis?

  27. 27.

    Can you discuss some of the weaknesses of a linear analysis model?

  28. 28.

    How do you deal with an unbalanced binary classification when analyzing a data set?

  29. 29.

    What are some of the differences between a histogram and a box plot?

  30. 30.

    Can you define cross-validation and describe how you will use this process when analyzing a data set once working here at Microsoft?