Straive Data Science Consultant Interview Questions and Answers

Q1. Gen AI projects
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Q2. Architecture of projects I worked
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DSA and ML, AI, Coding question

Q1. Case study which was easy
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Q1. In depth questions on ML
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Q1. Past projects of machine learning
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Developed a predictive model for customer churn using machine learning algorithms.
• Used Python and scikit-learn library for data preprocessing and model building

• Performed feature engineering to improve model performance

• Evaluated model performance using metrics like accuracy, precision, and recall
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Q2. Distributed computing and spark questions
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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
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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
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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
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Basic aptitude , tech aptitude

Q1. What is overfitting
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Q2. How to handle missing values
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2hrs - sections include aptitude, machine learning, deep learning and two easy python coding questions

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