IBM Consulting Data Scientist Interview Questions and Answers

Q1. Why do you want to for PWC?
Add your answer

Q1. Write a prompt to extract key Personal Identifiable Information given a resume
Ans. 
Extracting key Personal Identifiable Information from a resume prompt
• Look for information such as full name, address, phone number, email address, date of birth, and social security number

• Utilize natural language processing techniques to identify patterns and structures in the text

• Consider using regular expressions to match specific formats of personal information

• Ensure data privacy and security measures are in place w
Answered by AI
Add your answer

Q1. Question were asked pertaining to Mathematics behind ML algorithm
Add your answer

Q1. Scenario based NLP Machine Learning Question
Add your answer

Q1. Joining and salary Negotiations
Add your answer

Q1. How do you handle outliers? How to handle imbalance dataset? Feature engineering techniques?
Ans. 
Outliers can be handled by removing, transforming or imputing them. Imbalanced datasets can be handled by resampling techniques. Feature engineering involves creating new features from existing ones.
• Outliers can be removed using statistical methods like z-score or IQR.

• Outliers can be transformed using techniques like log transformation or box-cox transformation.

• Outliers can be imputed using techniques like mean imputat...read more
Answered by AI
Add your answer

Q1. 1. Explain the project in detail 2. Explain me your 5 favourite models 3. Questions on probability
Add your answer

Q1. It was a HR round and HR has asked me what's your salary expectations.
Add your answer

It was good , basic projects and coding was asked

Q1. 2 round technical interview, both of them about ML and last one concerning statistics and ML.
Add your answer
Q2. What is linear regression?
Ans. 
Linear regression is a statistical method to model the relationship between a dependent variable and one or more independent variables.
• It assumes a linear relationship between the variables

• It is used to predict the value of the dependent variable based on the independent variable(s)

• It can be simple linear regression (one independent variable) or multiple linear regression (more than one independent variable)

• It is commo...read more
Answered by AI
Add your answer
Q3. Question regarding confusion matrix?
Add your answer
Q4. Name various ML algorithm?
Ans. 
ML algorithms are used to train models on data to make predictions or decisions. Some popular ones are SVM, KNN, and Random Forest.
• Support Vector Machines (SVM)

• K-Nearest Neighbors (KNN)

• Random Forest

• Naive Bayes

• Decision Trees

• Linear Regression

• Logistic Regression

• Neural Networks

• Gradient Boosting

• Clustering Algorithms (K-Means, Hierarchical)

• Association Rule Learning (Apriori)

• Dimensionality Reduction Algorithms (PCA, LDA)

• Reinf
Answered by AI
Add your answer