Dun & Bradstreet Data Scientist Interview Questions and Answers

Q1. How to treat multicollinearity, imbalanced dataset
Ans. 
Multicollinearity can be treated by using techniques like feature selection, PCA, or regularization. Imbalanced datasets can be addressed by resampling techniques like oversampling or undersampling.
• For multicollinearity, consider using techniques like feature selection to remove redundant variables, PCA to reduce dimensionality, or regularization like Lasso or Ridge regression.

• For imbalanced datasets, try resampling te...read more
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Q1. Logistic regression in detail
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Logistic regression is a statistical model used to predict the probability of a binary outcome based on one or more predictor variables.
• Logistic regression is used when the dependent variable is binary (0/1, True/False, Yes/No, etc.)

• It estimates the probability that a given observation belongs to a particular category.

• The output of logistic regression is a probability score between 0 and 1.

• It uses the logistic function...read more
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Q2. Project related questions based on Machine learning
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Q1. Past projects of machine learning
Ans. 
Developed a predictive model for customer churn using machine learning algorithms.
• Used Python and scikit-learn library for data preprocessing and model building

• Performed feature engineering to improve model performance

• Evaluated model performance using metrics like accuracy, precision, and recall
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Q2. Distributed computing and spark questions
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Q1. SQL basics Python Basics Linux Basics
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Q2. Questions on date and time and joins.
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Q1. Describe yourself briefly about your experience
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Q2. Tell about your current company
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Q1. Key ratios and Industry related question
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Q2. Profit ratio, leverage ratio
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3 SQL questions were given

Q1. It was based upon my work experience and technical questions from SQL
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Q1. Salary discussion
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Q1. Tell me about yourself and work experience
Ans. 
I am a dedicated professional with 5 years of experience in marketing and project management.
• Worked in marketing for a tech company for 3 years

• Managed multiple projects simultaneously

• Strong communication and organizational skills

• Experience with data analysis and reporting

• Led successful marketing campaigns resulting in increased sales
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