Practice 30 Data Scientist interview questions covering machine learning, statistical modeling, and technical problem-solving.
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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.
"Experience has taught me that as hard as we try, we will still occasionally make mistakes. What's important is turning a failure into a learning opportunity. I once was assigned a project on which the data set was small and the anticipated results were easy to predict. I opted to utilize a simple approach and manual analysis methods instead of following protocol and using automated tools. I thought this would save time since the outcome was predictable. As I progressed through the analysis, it became apparent that the project was more complex than originally thought and the outcome was not as predictable. I had to restart the project, losing time and the resources I had already invested in the project. I learned to not cut corners and always follow protocol because eventually, I would have to anyway. "

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 a Behavioral question, which the interviewer will use to determine how you dealt with a specific issue in the past and how you would deal with it if you encountered it again while working for their organization. Behavioral questions are best answered by using the STAR format. STAR stands for Situation, Task, Action, and Results. Using this format will help you organize your answer and lead the interviewer through your story in a systematic manner.

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.
"In my current position, we performed analysis on a large set of data to determine why the company didn't achieve the results they expected from a major initiative they had implemented (Situation). Management had a hypothesis and expected the analysis to confirm it (Task). We completed the analysis, but the data led us to reach a different conclusion (Action). My colleagues and I repeated the analysis but used a modified data set and different analytical tools, and this time, the results matched the original assumptions. However, when management implemented changes based on this study, the results were the same as before (Results). I learned to be true to the methodology and let the results speak for themselves so the problem can be accurately identified and addressed."
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Written by William Swansen
30 Questions & Answers • Data Scientist

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