Microsoft Data Scientist Mock Interview

Master 30 Microsoft Data Scientist interview questions covering machine learning, Azure, and statistical modeling.

WRITTEN BY WILLIAM SWANSEN
QUESTION 30 OF 30

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

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30 Microsoft Interview Questions & Answers

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01 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? EXPERIENCE 02 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? EXPERIENCE 03 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? COMPATIBILITY 04 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. ACCOMPLISHMENT 05 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? CREATIVE THINKING 06 What data visualization tools do you have experience using? Which one is your favorite to use and why? EXPERIENCE 07 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. EXPERIENCE 08 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? BEHAVIORAL 09 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? EXPERIENCE 10 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. EXPERIENCE 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. CREATIVE THINKING 12 What experience do you have conducting text analytics? Describe a project you worked on that required text analytics. EXPERIENCE 13 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? EXPERIENCE 14 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. CREATIVE THINKING 15 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? BEHAVIORAL 16 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? CREATIVE THINKING 17 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? COMPATIBILITY 18 A a Data Scientist, how do you employ statistics to analyze data and develop business recommendations? BEHAVIORAL 19 What is Data Cleansing and why is it important in Data Analysis? EXPERIENCE 20 Can you describe how Data Analysis is used by businesses and other organizations like Microsoft? EXPERIENCE 21 Can you describe some of the steps you take to ensure that a regression model fits the data? BEHAVIORAL 22 What is a decision tree, and how would you use this in your job as a data scientist here at Microsoft? EXPERIENCE 23 Do you follow the hypothesis that many small decision trees are more accurate than one large one? EXPERIENCE 24 In your opinion, is mean square error a good or bad measure of model performance? PERSONAL 25 What are some of the assumptions required to accurately perform a linear regression analysis? EXPERIENCE 26 Do you perform data wrangling and data cleaning before applying machine learning algorithms to your data analysis? BEHAVIORAL 27 Can you discuss some of the weaknesses of a linear analysis model? EXPERIENCE 28 How do you deal with an unbalanced binary classification when analyzing a data set? BEHAVIORAL 29 What are some of the differences between a histogram and a box plot? CREATIVE THINKING 30 Can you define cross-validation and describe how you will use this process when analyzing a data set once working here at Microsoft? BEHAVIORAL

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William Swansen
Written by William Swansen
30 QUESTIONS & ANSWERS · MICROSOFT
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