Incedo Data Scientist Interview Questions and Answers

Python questions moderate to difficult

Q1. Introduction about self
Ans. 
I am a data scientist with a background in statistics and machine learning.
• I have a Master's degree in Data Science from XYZ University.

• I have experience working with Python, R, and SQL for data analysis.

• I have worked on projects involving predictive modeling and data visualization.

• I am passionate about using data to drive business decisions and solve complex problems.
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Q2. Python basics like list, dictionary
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SQL, Python and Apti ques

Q1. Have given Python question to print a pattern
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Q2. Some ML algo questions
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Q1. Why u are looking for job change
Ans. 
Seeking new challenges and growth opportunities in a different environment.
• Looking for new challenges to enhance my skills and knowledge

• Seeking growth opportunities that align with my career goals

• Interested in exploring different work environments and cultures
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Asked 2 to 3 python coding question...

Q1. What is random forest
Ans. 
Random forest is an ensemble learning method used for classification and regression tasks.
• Random forest is a collection of decision trees that are trained on random subsets of the data.

• Each tree in the random forest independently predicts the target variable, and the final prediction is made by averaging the predictions of all trees.

• Random forest is robust to overfitting and noisy data, and can handle large datasets wi...read more
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Q2. Explain lasso in feature selection
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Lasso is a feature selection technique that penalizes the absolute size of the regression coefficients.
• Lasso stands for Least Absolute Shrinkage and Selection Operator

• It adds a penalty term to the regression equation, forcing some coefficients to be exactly zero

• Helps in selecting the most important features and reducing overfitting

• Useful when dealing with high-dimensional data

• Example: In a dataset with multiple feature...read more
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Q1. Questions on MLP, ML
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Q1. What are the relevant projects in Data science & expertise in whatt all tools & technologies
Ans. 
Relevant projects in Data Science and expertise in tools and technologies
• Projects: Predictive modeling, Natural Language Processing, Computer Vision, Recommender Systems, Time Series Analysis

• Tools: Python, R, SQL, Tableau, Hadoop, Spark, TensorFlow, Keras, Scikit-learn

• Technologies: Machine Learning, Deep Learning, Big Data, Cloud Computing, Data Visualization
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Q1. He asked only coding question in Python & time duration is less & expectations are pretty unclear .
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Platform HackerEarth
9 Questions
2 Coding Questions on Python based on Dynamic Programming
7 Questions MCQ on Data Science and SQL

Q1. Data Science Projects discussion Python Coding by sharing screen
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Q1. Data Science Projects Detailed Questions
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Q2. In Depth Knowledge on any one of your project.
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Q3. Cross Questioning on Regression, Classfication Problems. Dummy Variable Trap Statistics Questions
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Q4. Questions on Deep Learning Models working and architecture like RNN Exploding/Vanishing Gradient Problem, Solutions like LSTM, CNN model working and different terminologies used.
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Q1. Again this round was pure Technical. All questions were on Data Science Projects and scenario based. 2 Questions on Probability and puzzle based.
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Q1. Final Round Discussion about Company's Policies and Roles. Your Expectations from the company, the kind of role you are looking for and why Tiger.
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