LatentView Analytics Junior Data Analyst Interview Questions and Answers

Q1. Self intro and technical questions
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Q1. Its all about statistical analysis
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Easy question was asked along with some aptitude questions.

Q1. Explain your project and the challenge you faced while doing the project?
Ans. 
Developed a predictive model for customer churn in a telecom company.
• Collected and cleaned customer data including demographics, usage patterns, and customer service interactions.

• Used machine learning algorithms such as logistic regression and random forest to predict customer churn.

• Challenges faced included imbalanced dataset, feature selection, and model evaluation.

• Implemented techniques like SMOTE for handling imbal...read more
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Q2. Basic join questions of SQL were asked
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Q1. Few dax and sql queries
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Q1. Salary discussion
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Q1. How you will be handling the projects
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Was maths quants etc

Q1. Problem solving on the spot
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It consisted verbal, logical , quant, 1 programming question & 1 guesstimate

Some english communication skills were tested

Pair Sum
1hr 45 mins

Q1. Guesstimate certain situations
Ans. 
Estimate the number of cars passing through a busy intersection in a day
• Estimate the average number of cars passing through the intersection per hour

• Consider peak traffic hours and adjust the estimate accordingly

• Factor in any special events or holidays that may affect traffic flow
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Q2. Puzzle problem with various modification
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Q1. Find the customer_id with maximum number of purchases consecutively?
Ans. 
Customer_id with maximum consecutive purchases
• Identify consecutive purchases for each customer

• Track the maximum consecutive purchases and corresponding customer_id

• Consider edge cases like ties or no consecutive purchases
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Q2. Find the product_id that got returned more than 10 times in a month and more than 3 times in a year?
Ans. 
Identify product_id with more than 10 returns in a month and 3 returns in a year.
• Filter the dataset by returns in a month and returns in a year

• Group the data by product_id and count the number of returns

• Identify product_id with counts exceeding the thresholds
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