Keyrus Mock Interview

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

Keyrus was updated by on February 28th, 2019. Learn more here.

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?

"In my eyes, data cleansing practices are an important part of my job duties and responsibilities. At the high level, I start with a data cleansing strategy, so I know what the goals and expectations are for the data cleansing initiative. Here is a list of best practices that I follow that has helped me become a better data consultant.

1. Develop a data quality plan - (Create data KPI's, know where data errors occur, determine where the data is coming from, and perform root cause analysis on data health).
2. Standardize customer contact data - (Check important data at the point of entry and create a standard operating procedure).
3. Validate and verify the accuracy of data - (Use manual, web, and email verification).
4. Identify duplicate entries - (Manual and automated systems).
5. Append data for accuracy - (Company name, contact first name and last name, title, phone, email, location, revenue, product lines, company stock, etc.)."

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28 Keyrus Interview Questions & Answers

Below is a list of our Keyrus SA interview questions. Click on any interview question to view our answer advice and answer examples. You may view 5 answer examples before our paywall loads. Afterwards, you'll be asked to upgrade to view the rest of our 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?