L&T Finance Data Analyst Interview Questions and Answers

Q1. Common ways to evaluate Time Series model
Ans. 
Common ways to evaluate Time Series model include AIC, BIC, RMSE, MAE, ACF, PACF, etc.
• Use Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) to compare models

• Calculate Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) to assess model accuracy

• Analyze Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) to check for autocorrelation in residuals
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Q2. Best ways to handle multicollinearity
Ans. 
Use techniques like feature selection, regularization, PCA, and VIF to handle multicollinearity.
• Perform feature selection to choose the most relevant variables for the model.

• Apply regularization techniques like Lasso or Ridge regression to penalize high coefficients.

• Utilize Principal Component Analysis (PCA) to reduce dimensionality and decorrelate variables.

• Check for Variance Inflation Factor (VIF) to identify highly
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Q1. Write a function taking input as string and output a dictionary which will give key as characters in these string and values as their frequency of occurrence
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Q2. TF IDF in NLP
Ans. 
TF IDF is a technique used in NLP to measure the importance of a word in a document within a collection of documents.
• TF IDF stands for Term Frequency-Inverse Document Frequency.

• It is used to determine how important a word is in a document relative to a collection of documents.

• TF IDF is calculated by multiplying the term frequency (TF) of a word in a document by the inverse document frequency (IDF) of the word across al...read more
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Create data frame, make histogram

Q1. He asked me to rate my sql and python out of 5 and gave me a scenario and asked to write a sql for it, it was basic left join and case statement question
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Q1. This round was basically discussion round with the interviewer, he asked me what i work in and what thing do i take care off as a data scientist
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Q1. Why are you choosing this job?
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Q2. What do you have qualification to get this job
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Q1. About technical skills
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Data related to finance

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Questions on Prob Stats, ML

Q1. Models you have worked on
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Q2. Internship Experience
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