L&T Finance Senior Data Scientist Interview Questions and Answers

Had three coding problems which was each

Q1. What are windows function in SQL
Ans. 
Window functions in SQL are used to perform calculations across a set of table rows related to the current row.
• Window functions are used to calculate values based on a set of rows related to the current row.

• They allow you to perform calculations without grouping the rows into a single output row.

• Examples of window functions include ROW_NUMBER(), RANK(), DENSE_RANK(), and NTILE().
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Q1. What are different algorithm in clustering?
Ans. 
Different clustering algorithms include K-means, DBSCAN, Hierarchical clustering, and Gaussian Mixture Models.
• K-means: partitions data into K clusters based on centroids

• DBSCAN: density-based clustering algorithm

• Hierarchical clustering: builds a tree of clusters

• Gaussian Mixture Models: assumes data points are generated from a mixture of Gaussian distributions
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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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Simple Python Coding Test focused on pandas and sql queries as well

Questions on Prob Stats, ML

Q1. Models you have worked on
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Q2. Internship Experience
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Had three coding problems which was each

Q1. What are windows function in SQL
Ans. 
Window functions in SQL are used to perform calculations across a set of table rows related to the current row.
• Window functions are used to calculate values based on a set of rows related to the current row.

• They allow you to perform calculations without grouping the rows into a single output row.

• Examples of window functions include ROW_NUMBER(), RANK(), DENSE_RANK(), and NTILE().
Answered by AI
Add your answer

Q1. What are different algorithm in clustering?
Ans. 
Different clustering algorithms include K-means, DBSCAN, Hierarchical clustering, and Gaussian Mixture Models.
• K-means: partitions data into K clusters based on centroids

• DBSCAN: density-based clustering algorithm

• Hierarchical clustering: builds a tree of clusters

• Gaussian Mixture Models: assumes data points are generated from a mixture of Gaussian distributions
Answered by AI
Add your answer