DS Group Data Scientist Interview Questions and Answers

Q1. Resume projects
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Q2. Logistic regression
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Q1. ML questions- Logistic regression derivation
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Forecasting of products demands

Q1. ML questions and project discussion
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Every participant was allowed to speak in sequential matter on a given ethics based imaginary scenario.

Q1. How to handle missing data in a dataset?
Ans. 
Missing data can be handled by imputation, deletion, or using algorithms that can handle missing values.
• Imputation: Fill missing values with mean, median, mode, or using predictive modeling.

• Deletion: Remove rows or columns with missing values.

• Algorithms: Use algorithms like Random Forest, XGBoost, or LightGBM that can handle missing values.

• Consider the reason for missing data and choose the appropriate method for handl
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Q2. What is Random Forest Classifier?
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Random Forest Classifier is an ensemble learning method that builds multiple decision trees and merges them to improve accuracy.
• Random Forest is a collection of decision trees that work together to make predictions.

• Each tree in the Random Forest is built using a subset of the training data and a random subset of features.

• The final prediction is made by aggregating the predictions of all the individual trees, usually th...read more
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Q1. How to choose a project out of the 2 for execution in your organization?
Ans. 
Choose the project based on alignment with organizational goals, available resources, and potential impact.
• Consider the alignment of the project with the organization's goals and objectives.

• Evaluate the available resources such as data, expertise, and time for each project.

• Assess the potential impact of each project on the organization's success and growth.

• Prioritize projects that have clear deliverables, measurable ou...read more
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Q2. What would you do if your manager is opposed to execution of a project?
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I would try to understand the reasons behind the opposition and work towards finding a solution that addresses concerns.
• Initiate a discussion with the manager to understand their concerns and reasons for opposition

• Present a detailed analysis of the project, highlighting its potential benefits and addressing any potential risks or drawbacks

• Propose alternative solutions or adjustments to the project plan that may allevia...read more
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Written test testing logical abilities

Q1. Asked basics of ML
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Q2. Additionally asked basic statistics based questions
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Data Science MCQ questions

Building a baseline ML model with EDA etc.

Q1. How do you analyse outliers?
Ans. 
Outliers can be analyzed using statistical methods like Z-score, IQR, or visualization techniques like box plots.
• Calculate Z-score and identify data points with Z-score greater than a certain threshold as outliers.

• Use Interquartile Range (IQR) to detect outliers by identifying data points outside 1.5 * IQR range.

• Visualize data using box plots to identify any data points that fall outside the whiskers.

• Consider domain kn...read more
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Q2. Tell me about a time when what you found did not match expectation with what you thought analysing the dataset.
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Q1. Why Unilever now?
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Q2. Where do you see yourself in 5 years?
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Q1. Describe about yourself and why you want to join us
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