WRITTEN TEST: 

Online Test

• Conducted on the DoSelect platform.
• MCQ Test

GROUP DISCUSSION: 

SKILLS REQUIRED

• Python
• SQL
• Machine Languages

INTERVIEW GUIDELINES

Round 1 : Technical Interview 1

• Checks basic understanding of ML
• Previous projects
• Live coding

Questions

• Explain gradient descent.
• What is the random forest technique?
• What is overfitting?
• What is the tradeoff between bias and variance? Explain giving an example.
• Which is better and why: Bagging or Boosting?
• How to predict room occupancy based on environmental factors.
• Write a Python code to model the prediction system for predicting marks of a student in Maths exam, based on his marks in other subjects.

Round 2 : Technical Interview 2

• Checks basic understanding of ML
• Business problems to check approach

Questions

• What is the vanishing gradient problem and how do we overcome that?
• Which activation function can’t be used at the output layer to classify an image?
• Is K-fold cross-validation linear in K, quadratic in K, cubic in K or exponential in K?
• What is Backpropagation in NN ?
• Explain the pros and cons of random forest.
• How can you reduce overfitting of a random forest model?
• What is Bais and Variance TradeOff?

Round 3 : Technical Interview 3

• Technical questions from resume
• Business acumen testing through data science case studies

Questions

• Explain word2vec to a non-technical person.
• How to check wine quality using knn classifier?
• Define precision, recall, homoscedasticity and autocorrelation.
• What are various evaluation parameters of regression and classification to evaluate the model?
• How will you handle class imbalance problems? What are various approaches?
• How will you decide the number of clusters in k means?
• How to reduce the number of variables in Logistic regression and random forest?

Round 4 : HR Interview

• Basic HR questions

Questions

• Why do you want to work for Fractal?
• What are your short-term and long-term goals?
• Explain your end to end Data Science projects.
• What are the challenges you faced during your previous projects? How did you overcome them?
• What are the challenges that you have faced in your professional life?
• What are your USPs?
• Where do you feel you should improve yourself?
• What technologies have you worked with in your previous projects?

MPLOYEE.ME TIPS

• The key to qualifying the written test is time management.