Crisil Data Analyst Intern Interview Questions and Answers

Q1. Can you elaborate on your work experience?
Ans. 
I have 5 years of experience in analyzing large datasets to extract valuable insights and make data-driven decisions.
• Analyzed customer behavior data to optimize marketing strategies

• Built predictive models to forecast sales trends

• Utilized machine learning algorithms to improve product recommendations

• Presented findings to stakeholders in a clear and actionable manner
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Q2. What questions were asked regarding your work experience?
Ans. 
Questions related to work experience in data science field.
• Asked about previous projects worked on

• Inquired about specific data analysis techniques used

• Discussed challenges faced and how they were overcome
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Q1. Explain any ML model.
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Q2. Create Dataframe from two lists.
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Q1. Explain the RAG pipeline?
Ans. 
RAG pipeline is a data processing pipeline used in data science to categorize data into Red, Amber, and Green based on certain criteria.
• RAG stands for Red, Amber, Green which are used to categorize data based on certain criteria

• Red category typically represents data that needs immediate attention or action

• Amber category represents data that requires monitoring or further investigation

• Green category represents data that...read more
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Q2. Explain Confusion metrics
Ans. 
Confusion metrics are used to evaluate the performance of a classification model by comparing predicted values with actual values.
• Confusion matrix is a table that describes the performance of a classification model.

• It consists of four different metrics: True Positive, True Negative, False Positive, and False Negative.

• These metrics are used to calculate other evaluation metrics like accuracy, precision, recall, and F1 s...read more
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Questions based on ML,PYTHON, DATA VISUALIZATION

Q1. What is TF-IDF IN NLP
Ans. 
TF-IDF is a numerical statistic that reflects the importance of a word in a document relative to a collection of documents.
• TF-IDF stands for Term Frequency-Inverse Document Frequency

• It is used in Natural Language Processing (NLP) to determine the importance of a word in a document

• TF-IDF is calculated by multiplying the term frequency (TF) by the inverse document frequency (IDF)

• It helps in identifying the most important
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Q2. Python coding questions based on list
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Excel data analytics case

Q1. Data analytics, data visualisation tools
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SQL, Python coding …

Along with coding round..there's a communication test at the end

Q1. There's ntg to ask about technical for me..
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Q2. Behavioural questions
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