Bharat Financial Inclusion Data Scientist Interview Questions, Process, and Tips

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

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Multiple Choice Questions

Q1. Why do you want to join us
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Q1. What is life like
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Q2. What did your dad do
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Q1. It was more related to my projects
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Q2. Asked questions on PCA,KNN and Elbow method .
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Q1. Asked SVM and Logistic regression, their applications and real life uses
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Q2. Matrix formation of a knockout Tournament
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Asked questions of finance and aptitude

Q1. What is machine learning?
Ans. 
Machine learning is a branch of artificial intelligence that involves developing algorithms and models that enable computers to learn from and make predictions or decisions based on data.
• Machine learning is a subset of artificial intelligence that focuses on developing algorithms that can learn from and make predictions or decisions based on data.

• It involves training models on large datasets to recognize patterns and m...read more
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Q2. What do you know about SQL?
Ans. 
SQL is a programming language used for managing and manipulating relational databases.
• SQL stands for Structured Query Language

• It is used to retrieve and manipulate data in relational databases

• Common SQL commands include SELECT, INSERT, UPDATE, DELETE

• SQL can be used to create tables, indexes, and views

• Examples of SQL databases include MySQL, PostgreSQL, Oracle
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Q3. What you know about software Development?
Ans. 
Software development involves creating, designing, testing, and maintaining software applications.
• Software development includes coding, testing, debugging, and documenting software applications.

• Developers use programming languages like Java, Python, C++, etc. to write code.

• Agile and Waterfall are common software development methodologies.

• Version control systems like Git are used to manage code changes.

• Software developm...read more
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Q1. What are the algorithms you know in machine learning and their details ?
Ans. 
Various machine learning algorithms with brief details
• Supervised Learning: Linear Regression, Logistic Regression, Support Vector Machines (SVM), Decision Trees, Random Forest

• Unsupervised Learning: K-means Clustering, Hierarchical Clustering, Principal Component Analysis (PCA)

• Reinforcement Learning: Q-Learning, Deep Q-Networks (DQN)

• Neural Networks: Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), L
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Q2. Python questions
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1 hour coding test on intermediate python programming