Ola Cabs Junior Data Analyst Interview Questions and Answers

Based on uber, SQL queries, quantitative aptitude

Q1. SQL queries, Uber-specific case studies, Resume
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UBER- specific case studies

Q1. How do you gain experience in data analysis?
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Q2. What are your thoughts on the matter?
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Q3. What is algorithm
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Q1. What is a data structure?
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Q2. What are the different types of data structures available?
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SQL and Python coding test

Q1. Bagging vs Boosting
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Q2. Overfitting and Underfitting in GBDT
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Q1. Questions on Recent project
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Q2. Deep Learning vs classical ML
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The final output should encompass comprehensive research, a conclusion, and visual aids.

Covering algorithms and data structures, hosted on HackerRank with multiple programming language options.

Covering topics such as quantitative reasoning, logical reasoning, and verbal ability through multiple-choice questions.

Q1. Tell me about your projects?
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Q2. How do you approach the project if you are using logistic regression model?
Ans. 
Approach involves data preprocessing, model training, evaluation, and interpretation.
• Perform data preprocessing such as handling missing values, encoding categorical variables, and scaling features.

• Split the data into training and testing sets.

• Train the logistic regression model on the training data.

• Evaluate the model using metrics like accuracy, precision, recall, and F1 score.

• Interpret the model coefficients to under...read more
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Q1. What are you future goals?
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Q2. What would you do if your interested field doesnt have any work in the company?
Ans. 
I would seek opportunities to apply my skills in related fields within the company.
• Explore other departments or teams within the company that may have projects related to my field of interest

• Offer to collaborate with colleagues in different departments to bring a new perspective to their projects

• Seek out professional development opportunities to expand my skills and knowledge in related areas
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Q1. Explain all of decision tree and random forest?
Ans. 
Decision tree is a tree-like model of decisions and their possible consequences, while random forest is an ensemble learning method that builds multiple decision trees and merges them together.
• Decision tree is a flowchart-like structure where each internal node represents a decision based on an attribute, each branch represents the outcome of the decision, and each leaf node represents a class label.

• Random forest is a ...read more
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Q2. Some basic probability questions
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Q1. Projects Worked
Ans. 
I have worked on various projects involving data analysis, visualization, and interpretation.
• Developed predictive models using machine learning algorithms

• Performed data cleaning and preprocessing to ensure accuracy

• Created interactive dashboards for stakeholders to easily understand insights
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Q2. SQL functions used in the projects
Ans. 
Common SQL functions used in projects include COUNT, SUM, AVG, MAX, MIN, and GROUP BY.
• COUNT: Used to count the number of rows in a table.

• SUM: Used to calculate the sum of a column.

• AVG: Used to calculate the average value of a column.

• MAX: Used to find the maximum value in a column.

• MIN: Used to find the minimum value in a column.

• GROUP BY: Used to group rows that have the same values into summary rows.
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Q3. Machine learning alogriths
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