Morgan Stanley Interview Questions for a full-time job, by Sweata Sen, an alumna of ISI, Kolkata.

Role: Data Scientist under MRM (Model Risk Management)

Process: Two technical tests were taken, one was on quant and the other on R/Python programming. Then after passing these two tests, I was asked to give an interview.

## Placement Process

**Interview Questions: **

- Walk me through your resume.
- State the assumptions of linear regression.
- If the errors are correlated then what happens to the beta estimator?
- Suppose I have three variables a,b,c and while fitting the model, I found out that a and c are important. Then I realized that carelessly, I havenâ€™t included the variable d in the model. Now after fitting I found out that a and d are important. Why do you think this happened?

Now suppose I want to include 20 other variables and I want a clean model. What do I do now? (I answered about variable selection.)

- Which one would you choose – Lasso or ridge?
- What about stepwise selection models? What is the kind of stepwise regression we usually do? When do we use forward stepwise regression and when do we use backward stepwise regression?
- Do you know about neural networks? What is an activation function? What happens if we use a step activation function other than sigmoid activation function? Advantages or disadvantages of one over the other.
- Suppose you have an equilateral triangle inscribed within a circle. You choose a vertex and start drawing infinitely many lines to different points on the circumference. What is the probability that if I choose one line, it is longer than one side of the triangle?
- Tell me about you as a person. State your three strengths and three weaknesses.
- Do you have any questions for me?

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