Technical Questions: Describe a data science project you've worked on. What was your role and what were the outcomes? How do you clean and preprocess data before building a model? Explain the difference between supervised and unsupervised learning. Give examples of each. What is cross-validation, and why is it important in machine learning? How do you handle missing or incomplete data in a dataset? What evaluation metrics have you used to assess the performance of a machine learning model? Can you explain the bias-variance tradeoff? How do you address it in your models? What is regularization in machine learning? Why is it important? Explain the process of feature selection. How do you determine which features are important in a model? How do you interpret the results of a logistic regression model? Behavioral Questions: Tell me about a time when you had to work with a large, complex dataset. How did you approach it? Give an example of a problem you faced in a data science project and how you solved it. How do you stay updated with the latest trends and developments in the field of data science? Describe a situation where you had to work under pressure to meet a deadline. How did you handle it? How do you communicate your findings from a data science project to non-technical stakeholders? Tell me about a time when you had to collaborate with a team to achieve a goal. What was your role, and what was the outcome? What motivates you as a data scientist? How do you prioritize multiple tasks or projects? Case Study or Problem-Solving Questions: You are given a dataset of customer transactions. How would you segment the customers based on their purchasing behavior? You have a dataset with missing values. How would you impute the missing data? Imagine you have a dataset with a high class imbalance. How would you address this issue before building a classification model? Given a dataset of tweets, how would you perform sentiment analysis? You are asked to predict the sales of a product for the next quarter. What approach would you take? General Questions: Why do you want to work at Accenture? What do you know about our data science projects or initiatives? Do you have experience working in a consulting environment? How do you think it differs from working in other industries? What are your salary expectations? Do you have any questions for us?