L&T Finance Internship Experience
Student Name: Sai Goutham Pydi
Current Course: MSQE
Degree Before Masters: BS-MS in Mathematics
Company Name: L&T Finance
Job Role: Intern Analytics AI/ML
Duration of the Job Role: 2-3 Month Internship
Hiring Process Overview:
CV shortlisting, One Aptitude round and one interview round
Questions Asked in Online Aptitude Test (if applicable):
To begin with there were 60 questions for 60 min, the test had four sections Quantitative Ability, Verbal Ability, Logical Reasoning and then ML questions(15 ques)
Number of Interview Rounds:
1
Questions Asked in Round 1:
The interview began with the HR asking about my knowledge of the company and posing a few generic HR questions on teamwork and similar topics. The technical round questions are summarized below:
- Explain your Econometric Analysis Project (I worked on the Periodic Labour Force Survey data).
- What problems did you face when working with the data? How did you deal with missing values in the dataset?
- Why did you choose Mean and Median to fill those values? Why not just skip those data points?
- Where does the Mean outperform the Median as a better descriptive statistic and vice versa?
- What measure did you use to assess your model?
- What were the assumptions of your model (Linear Regression with ridge regularization), and did you check those?
- What is the difference between R^2 and adjusted R^2?
- What is RMSE? How did you choose your model among others(different regularization parameters)? Did you have a cross-validation set and which error do you report?
The interviewer then asked about my SQL skills, to which I truthfully admitted that I don’t know SQL but am comfortable with pandas.
The subsequent questions included:
- What is the difference between loc and iloc in pandas?
- If we had a column (of a DataFrame) with categorical variables, what pandas method would you use to get the frequency of occurrence of the categorical variable? (Hint: pd.Series.value_counts())
The final question from the technical interviewer was: Why do you want to get into data science?
Questions Asked in Round 2:
Questions Asked in Further Rounds:
Job Role Experience:
Suggestions for Candidates (including resources, books, websites):
- Be well versed with your projects, they will grill you on those.
- If its a Data Science role, revise your ML basics.
Additional Resources:
Previous Job Role (if applicable):