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Keyrus Mock Interview

To help you prepare for a Keyrus job interview, here are 28 interview questions and answer examples.

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Question 1 of 28

Could you name a few data cleansing best practices that you follow, and how this has helped you become a better Data Consultant?

A lot of companies ask their technology employees about why data cleansing matter to them. The answer is simple. Good quality data will help a company identify potential customers, provide better customer service, run better quality sales and marketing campaigns, and know how much they are spending and tracking to determine ROI's.

Data Consultants should have expertise with a variety of business intelligence tools like Informatica, Power BI, Cognos, and Microstrategy. All these tools help the company manage data so it can be used within the company for many purposes.

What the hiring manager is seeking out of this question is best practices that you follow. Everyone seems to have a way of doing things their way, and because it's their way, it's not necessarily the best way. This is precisely why the hiring manager wants to hear about your best practices method. Has your method made you a better consultant? The best practices method that you share should convey a message of progressive learning and experience gained in the field while being given more responsibilities for larger and more complex projects. Don't forget to list your best practices and the data cleansing strategy that you use as well.

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28 Keyrus Interview Questions & Answers

  • 1. Could you name a few data cleansing best practices that you follow, and how this has helped you become a better Data Consultant?

  • 2. Explain what the difference is between Data Mining and Data Analytics, and tell me how you have used both in your recent projects?

  • 3. When have you worked amongst a diverse group of people?

  • 4. Walk me through your post-secondary education and how it will help you in your career with Keyrus.

  • 5. Help me understand your standards for success in your last job. Please describe what you did to attain those standards, and if you fell short of expectations, what did you do to remedy the problem?

  • 6. Describe a time you helped implement a new technology for your client. Did you encounter any challenges, and how did you address them?

  • 7. Tell me about a time where you made a great recommendation that you think would have greatly benefited your client, but they just didn't like it. What approach did you take to convince them?

  • 8. Big Data can be an efficient tool to monitor and grow a business, but can have challenges if not properly implemented. What challenges have you encountered while working with big data?

  • 9. What characteristics or events have contributed towards your success as a leader?

  • 10. When have you had to change a major component of your project due to new information being presented?

  • 11. What is your knowledge of imputation? Would you kindly list different types of imputation techniques, and which method you find to be most favorable for your environment?

  • 12. How would your most recent manager describe you?

  • 13. Would you be willing to work over 40 hours a week?

  • 14. Describe a situation where a project you were managing failed. What did you learn about this failure, and were you able to salvage or turn it around?

  • 15. What questions do you have for me about Keyrus?

  • 16. We're a company of innovative thinkers; we rely upon our innovative thinking to solve client problems. Tell me about a time when you came up with a breakthrough idea that was not obvious to others. Describe your idea and how you developed it?

  • 17. Your customer wants you to explain the benefits of the Big Data model you developed, how do you communicate the insights they can use for their business?

  • 18. When you suffer a setback, how does that emotionally affect you and your work?

  • 19. Have you ever broken a confidentiality agreement?

  • 20. What are your salary expectations?

  • 21. When designing a machine learning model, what in your opinion is more important, model performance or model accuracy, and why?

  • 22. Our clients have high expectations of our work, tell me about a time you worked with challenging time constraints, but were still able to exceed client expectations.

  • 23. A client wants to implement a new software system that was recommended by a different division of the same company. How do you evaluate it to ensure it's the right choice?

  • 24. Tell me about a time that you were assigned to manage a data analytics project. Walk me through the step-by-step process that you used to kick-off this project?

  • 25. What part of this career brings you the most stress?

  • 26. Describe to me your ideal employer.

  • 27. When dealing with data, in your opinion, is it better to have too many false positives, or too many false negatives? Please explain.

  • 28. The way we approach clients in our business is we identify client needs and recommend solutions to their needs. Tell me about a time when your knowledge and expertise allowed you to make a recommendation to resolve a problem or address a pain point?