About general knowledge and AI regulations.

Questions in step 1 with Senior Recruiter 1. The recruiter gives information about herself and the company 2. She may ask you if you know anything about our company, always do your research 3. Know the details about the job position. 4. Why are you interested in our company? 5. A question on Expected Compensation 6. Your current job and graduation date if you’re graduating Questions in step 2 with Operations Manager 1. Why do you want to work at WWT? 2. Questions about my Phd research topic, like why are researching that particular topic? 3. Tell me about yourself 4. How did you get to know about our company? Questions in step 3 with Senior DS 1. Tell me about yourself 2. Asked questions about my projects on my resume Anomaly detection project details Why we used Auto Encoders Why did we reduce the dimensionality of the data How did we deal with class imbalance What metric did you use to classify NLP project: What was the project about How did you vectorize the data: Talked about tfidf, lemmatization, and tokenization Why did you use the Random Forest classifier What metric did you use to evaluate the model F1 score, precision-recall, ROC-AUC Visual recognition project: Tell me about the project How did you deal with overfitting? Do you know anything about drop-out? 3. Why would you choose logistic regression over a random forest model? 4. Imagine you have a column with a categorical variable (like the type of vehicle, how would you handle such a variable? 5. Now say have a column for zip code, how would you deal with this 6. Brain teaser: draw a square of side 1 inch2 and draw a circle inside it such that the circle touches the side of the square Find the area of the circle Now imagine you don’t know the formula for the area of the circle How will you approximate the area of the circle? Imagine I give you a scissor and weighing scale, how will you find the area of the circle now? Questions in step 4 with Senior DS 1. Tell me about yourself 2.Questions about my projects on the resume similar to the last one and questions 3. If you want to perform Linear Regression would it be a problem if two features are pairwise-correlated? 4. If I say that the accuracy of a model is 98% would you be happy with this? 5. Can you estimate the number of flights that take off from an airport near you in one hour? 6. Probability: In an exam, there are 100 True False questions If a student didn’t study anything, how many questions quill he get correct? If someone who studied for the exam gets 75correct, how many questions did he know the answer to? 7. Why do you want to work at WWT and why consulting Data Science? Questions in step5 with Engagement Manager 1. Tell me about yourself 2. Why do you want to move from academia to consulting DS? 3. How do you deal with conflict at work 4. Very smart people are sometimes very egoistic, how do you deal with that? 5. How do you collaborate with a team 6. Do you have the opportunity to train people about your work Questions in step 6 with Senior DS Manager 1. Tell me about yourself 2. Going through my resume and asking questions About my research and projects About programming languages Have I used Docker, container Have I used AWS Used MS azure Have I used Tableau 3. Probability : same Question as the last one 4. Imagine a client comes to you and gives you a 5TB of the data file on Monday, you have a meeting with them on Friday, what questions are you going to ask them on Friday? 5. Imagine the earth as a perfect sphere: You move 10 miles south, 10 miles east, 10 miles north. Where should be your start point so that after following the directions above you get back to the same point Questions in step 7 with Chief Data Scientist 1. Explain the working of a Random Forest Tree for regression and a Classification model 2. Brain Teasers Say you have 9 coins, 8 out of them are similar in weight and 1 coin is a bit heavy and I give you a Balance scale How will you find out the heavy coin? How will you find the heavy coin in two iterations Water in a glass problem(remove half water every iteration) Ising model problem 3. Programming Languages IDE I used for programming Have I used Keras/TF/Sk-Learn and where? Are you familiar with NLP, tell me about a project you’ve worked on