This question is designed to evaluate your problem-solving abilities, resilience, and how you handle unexpected outcomes. When answering, choose a specific example where your analysis or model did not yield the expected results. Explain the context, what went wrong, and most importantly, the steps you took to identify the issue and rectify it. Highlight any lessons learned and how you applied them to future projects.
Example:
"In one of my projects, I developed a predictive model to forecast sales. Despite thorough data cleaning and feature engineering, the model's accuracy was significantly lower than expected. I revisited the data and discovered that a key variable had been incorrectly encoded. After correcting this and retraining the model, the accuracy improved substantially. This experience taught me the importance of double-checking data preprocessing steps and incorporating validation checks into my workflow."
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