Play Games Interview Questions
Position – Full-time Job
Profile – Data Scientist
Process – Case Study followed by 3 rounds of interview
Round 1 was a case study round. All of the students were given a separate case study chosen randomly. We needed to write our approach to solve the problem, as well we needed to write how we plan to do feature engineering, validate data science solutions and create pipeline architecture of the model deployment.
• First few questions were mainly focused on how I did feature selection in my internships and various college projects.
• What are VIF and BIC?
• For model selection in the case of linear regression, what do you plan to choose as your model selection criteria? BIC or MSE corresponding to a test dataset? Why?
• Will collinearity affect random forest?
• Explain how do convolutional neural networks work?
• What’s backpropagation and forward propagation?
• Is feature selection important in the case of tree-based models?
• For Image Recognition what loss function do you plan to choose and why?
• What’s stochastic gradient descent?
• What are different methods you can think of for detecting collinear variables in a dataset? What’s the most concrete method?
• Mainly focused on various case studies mostly relating to anomaly detection and feature selection in the case of Tree-Based models.
• What’s Isolation Forest?
• Tell me about yourself.
• What’s Data Science?
• Relation between Statistics and data science.
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