Quantiphi Analytics Solutions Private Limited 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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Q1. Dicision Tree algorithm
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Decision Tree algorithm is a supervised learning algorithm used for classification and regression tasks.
• Decision Tree algorithm is based on a tree-like model of decisions and their possible consequences.

• It uses a set of rules to split the data into branches and make predictions at the leaf nodes.

• The algorithm selects the best attribute to split the data based on certain criteria like information gain or Gini index.

• Deci...read more
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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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Coding test of 2 hours ,include model building

Q1. First Project explanation and in between that ask for project related questions and also asked basic ml to advance ml questions
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Q1. Machine Learning algorithms
Ans. 
Machine Learning algorithms are used to train models on data to make predictions or decisions without being explicitly programmed.
• Machine Learning algorithms can be categorized into supervised, unsupervised, and reinforcement learning.

• Examples of supervised learning algorithms include linear regression, decision trees, and support vector machines.

• Examples of unsupervised learning algorithms include k-means clustering, ...read more
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Q2. Overfitting and underfitting
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Q3. Questions related to the project
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Q1. Questions on project, how much time required for training model
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Q2. Version control, Flask/ Django, Cloud service experience
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