Practice 30 Data Scientist interview questions covering machine learning, statistical modeling, and technical problem-solving.
Question 12 of 30
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William Swansen has worked in the employment assistance realm since 2007. He is an author, job search strategist, and career advisor who helps individuals worldwide and in various professions to find their ideal careers.
"Text analysis is the process of examining written communications to discover trends or create meaning. It involves sentiment analysis, key phrase extraction, and entity recognition. It usually is used with customer communications to improve a product or service. While working on a recent project to determine which of our company's services customers found the easiest to use, I analyzed email exchanges between the sales team and their customers. The results revealed that while customer surveys indicated that one service was the most popular, the email exchanges found that the customers actually enjoyed using another service more. This enabled the company to adopt some of the features of this service to improve customer satisfaction with the other ones we offered."

William Swansen has worked in the employment assistance realm since 2007. He is an author, job search strategist, and career advisor who helps individuals worldwide and in various professions to find their ideal careers.
This is another technical question which the interviewer will ask to confirm your skills and experience as a Data Scientist. They want to ensure that you are qualified for the job and are familiar with a specific process that they use to analyze data to improve the results of their operations.

William Swansen has worked in the employment assistance realm since 2007. He is an author, job search strategist, and career advisor who helps individuals worldwide and in various professions to find their ideal careers.
"Text Analytics is the process of creating meaning out of written communications. A common usage of this is in a customer experience context - examining text that was written by, to, or about customers. This helps find patterns and topics of interest and then enables the organization to take action based on what it learns. While working on a recent project involving the review of a service our organization provides, I examined the email communications between our support team and the customers. My analysis identified a specific issue that customers inquired about frequently. We then reviewed the documentation related to this and realized that it was vague and somewhat confusing. After updating the information and performing subsequent text analysis, I confirmed that the number of customer inquiries about this issue had dropped by 70%."
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Written by William Swansen
30 Questions & Answers • Data Scientist

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