Idfy Data Scientist Interview Questions and Answers

Q1. Explain any Data Science project
Ans. 
Developed a predictive model to forecast customer churn for a telecommunications company.
• Identified key features such as customer tenure, monthly charges, and service usage

• Collected and cleaned data from customer databases

• Built a machine learning model using logistic regression or random forest algorithms

• Evaluated model performance using metrics like accuracy, precision, and recall

• Provided actionable insights to reduce
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Q2. Types of Error in Statistics
Ans. 
Types of errors in statistics include sampling error, measurement error, and non-sampling error.
• Sampling error occurs when the sample does not represent the population accurately.

• Measurement error is caused by inaccuracies in data collection or measurement instruments.

• Non-sampling error includes errors in data processing, analysis, and interpretation.

• Examples: Sampling error - selecting a biased sample, Measurement err...read more
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Q3. Types of Machine learning models
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Types of machine learning models include supervised learning, unsupervised learning, and reinforcement learning.
• Supervised learning: Models learn from labeled data, making predictions based on past examples (e.g. linear regression, support vector machines)

• Unsupervised learning: Models find patterns in unlabeled data, clustering similar data points together (e.g. k-means clustering, PCA)

• Reinforcement learning: Models le...read more
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Q4. Functions of pandas library, such as get_dummies()
Ans. 
get_dummies() function in pandas library is used to convert categorical variables into dummy/indicator variables.
• get_dummies() function creates dummy variables for categorical columns in a DataFrame.

• It converts categorical variables into numerical representation for machine learning models.

• Example: df = pd.get_dummies(df, columns=['column_name'])
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Q1. Machine learning algorithms
Ans. 
Machine learning algorithms are used to analyze data and make predictions or decisions without being explicitly programmed.
• Machine learning algorithms can be categorized into supervised, unsupervised, and reinforcement learning.

• Examples of machine learning algorithms include linear regression, decision trees, support vector machines, and neural networks.

• These algorithms learn from data to improve their performance over...read more
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Q2. SQL basics and basic knowledge of security products
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Q1. Very lengthy process and delayed a lot
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Q1. Tell me about your projects
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Q2. What do you know about mutual funds
Ans. 
Mutual funds are investment vehicles that pool money from multiple investors to invest in a diversified portfolio of securities.
• Mutual funds are managed by professional fund managers who make investment decisions on behalf of the investors.

• Investors can buy shares of mutual funds, which represent their ownership in the fund's portfolio.

• Mutual funds offer diversification, liquidity, and professional management to invest...read more
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Q1. Do you have prior experience with ML
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Q2. What are your long term plans
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Q1. Self intro , normal question like background
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Q1. About differ based on what the role you looking for , basically mutual fund questions and and Excel
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Konwledge of document and excell

Few questions were given on strings and linked list.

Is AI good or bad .

Q1. Mostly HR based questions.
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Q2. Some are related to our project's.
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1 hour 10 mins, MERN Stack, Face to Face. Mongodb, medium DSA Question, callback, eventloop, NodeJS asynchronous working