Dun & Bradstreet Data Scientist Intern Interview Questions and Answers

DSA and ML, AI, Coding question

Q1. Case study which was easy
Add your answer

Q1. In depth questions on ML
Add your answer

Sql, python, Statistics mcq, Aptitude test. These were medium level questions.

Q1. SQL and python, time complexity
Add your answer
Q2. Make 2 lists a=[1,2,3,4] b=[9,8,5,5,2,3,3,4,1,1,10,9,2,3,4,10,10,9,7,7,8] Write a program to remove duplicate of b and keep only those elements of b which are not present in a, and the final list should ...read more
Ans. 
Remove duplicates from list b, keep elements not in list a, and sort in ascending order.
• Create a set from list b to remove duplicates

• Use list comprehension to keep elements not in list a

• Sort the final list in ascending order
Answered by AI
View 1 more answer
Q3. SQL question Remove duplicate from a table tab1
Ans. 
Use the DISTINCT keyword in SQL to remove duplicates from a table.
• Use the SELECT DISTINCT statement to retrieve unique rows from the table.

• Identify the columns that should be used to determine uniqueness.

• Example: SELECT DISTINCT column1, column2 FROM tab1;
Answered by AI
View 1 more answer

Given 2 case studies on data science and asked different possibilities to improve the models.

How to work with imbalance dataset.
How to remove null values, what is features engineering.
What is PCA
What is the working of XGBOOST

Q1. What was last project, tell me in detail. There were different technical questions related to my project
Add your answer

Test consisted 7 sections which lasted for more than a hour. There were questions related to coding , sql , analytical questions etc.

1 python coding questions and 2 Sql question

2 case study question

Q1. This was the final round . Technical+HR .
Add your answer

Q1. Explain any ML model.
Ans. 
Random Forest is an ensemble learning method that builds multiple decision trees and merges them together to get a more accurate and stable prediction.
• Random Forest is a popular machine learning model used for classification and regression tasks.

• It works by creating multiple decision trees during training and outputs the mode of the classes for classification or the average prediction for regression.

• Random Forest is ro...read more
Answered by AI
Add your answer
Q2. Create Dataframe from two lists.
Ans. 
Creating a DataFrame from two lists in Python.
• Import the pandas library

• Create two lists of data

• Use pd.DataFrame() to create a DataFrame from the two lists
Answered by AI
Add your answer

I was asked to write SQL queries for 3rd highest salary of the employee, some name filtering, group by tasks.
Python code to find the index of the maximum number without using numpy.

Q1. Explain the Project undertaken during the research and follow-up questions
Add your answer

Q1. Write pandas query to separate the names as first and last name from the full name. Drop the duplicate columns and also the missing values. Write output for the Python code. Write SQL query to retrieve t...read more
Ans. 
Answering questions related to data science concepts and techniques.
• Recall is the ratio of correctly predicted positive observations to the total actual positives. Precision is the ratio of correctly predicted positive observations to the total predicted positives.

• To reduce variance in an ensemble model, techniques like bagging, boosting, and stacking can be used. Bagging involves training multiple models on different ...read more
Answered by AI
Add your answer

2hrs - sections include aptitude, machine learning, deep learning and two easy python coding questions

Q1. Resume scrutiny with projects and internships
Add your answer
Q2. How to measure 45 mins duration using two identical wires
Add your answer
Q3. Partition a round cake into eight equal parts within three cuts
Add your answer
Q4. 10 coins puzzle (5 heads up and 5 tails up)
Add your answer

Q1. Questions related to python basics.
Add your answer
Q2. Basic calculus to test math skills.
Add your answer
Q3. Machine learning metrics.
Add your answer

Q1. Policies, behavioral round.
Add your answer
Q2. Work culture and the selection process.
Add your answer
Q3. Discussion about previous employers and educational background.
Add your answer