Flipkart Data Analyst Interview Questions

Flipkart Data Analyst Interview Questions
Company – Flipkart
Designation – Data Analyst
Experience required – 0 to 4 Years
Topics to prepare – SQL, Project related, Case Study, MS Excel
Salary range – 10 to 30 LPA (One of our students received a CTC of 28 LPA including a 10% variable)


Flipkart Data Analyst Interview Questions

Flipkart Data Analyst Interview Questions – Rounds

1. Resume Screening & HR Round (1 round)

• HR Interview: The initial round focuses on understanding your background, qualifications, and why you are interested in the role at Flipkart. HR will also assess if you fit the company’s culture.

2. Technical Rounds (2-3 rounds)

These rounds will focus on your technical skills related to data analysis, statistics, and problem-solving abilities.

• SQL & Data Manipulation: You will be asked to write SQL queries, manipulate data sets, and perform data extraction. Proficiency in SQL is critical.
• Excel/Spreadsheets: You may be asked questions on data manipulation using Excel, including pivot tables, VLOOKUP, and other advanced functions.
• Statistics & Probability: Interviewers will test your understanding of statistical concepts like probability distributions, hypothesis testing, and A/B testing.
• Data Interpretation & Case Studies: You may be given a business problem and a dataset to analyze and derive insights, focusing on how you approach problem-solving using data.

3. Business Acumen & Problem-Solving (1 round)

• In this round, you will face questions on data-driven decision-making and how you derive insights from the data to impact the business. You’ll be assessed on your business understanding, ability to work with ambiguous problems, and drive actionable insights from data.

4. Behavioral Interview (1 round)

• This round focuses on your soft skills, leadership principles, teamwork, and how well you fit within the company’s culture. Flipkart often assesses behavioral aspects through situational questions based on past experiences.

5. Managerial/Leadership Round (Optional)

• In some cases, a round with the hiring manager may occur, where they assess your overall fit for the team and deeper alignment with Flipkart’s business goals and culture.

Summary:

• HR Screening: 1 round
• Technical Rounds: 2-3 rounds (SQL, statistics, data analysis)
• Business Acumen/Problem-Solving: 1 round
• Behavioral Interview: 1 round
• Managerial Round (Optional): 1 round

The entire interview process can take 2-4 weeks, depending on the role’s urgency and availability of interviewers.

Prepare for Flipkart Data Analyst Interview Questions

In the technical round for a Data Analyst role at Flipkart, the questions will focus on key areas such as SQL, statistics, data analysis, problem-solving, and tools like Excel or Python. Below are the different types of questions you can expect:

1. SQL Questions

SQL is a crucial part of the Data Analyst role. You will be tested on your ability to write efficient queries, manipulate data, and handle large datasets.

• Basic Queries:
  • Write a query to find the total number of orders placed in the last month.
  • How would you extract distinct values from a column in a table?
• JOINs:
  • Write a query to find the total sales for each customer using orders and customers tables.
  • How would you retrieve a list of products that have never been purchased, using products and orders tables?
• GROUP BY & Aggregate Functions:
  • Write a query to calculate the average order value per customer.
  • How would you find the top 5 best-selling products in the last year?
• Subqueries:
  • Write a query to find the second-highest salary from an employees table.
  • How would you retrieve customers who placed more than 3 orders?
• Window Functions:
  • Use a window function to rank products by their sales within each category.
  • How would you calculate a running total of sales for each day?
• Data Transformation:
  • Write a query to categorize orders based on the total amount spent (e.g., “Low”, “Medium”, “High”).
  • How would you replace null values in a column with a default value?

2. Excel/Spreadsheets Questions

Flipkart may test your Excel skills since it’s a common tool for data manipulation.

• Pivot Tables:
  • Create a pivot table to summarize sales by region and product category.
  • How would you use a pivot table to analyze monthly sales trends?
• Formulas:
  • Explain how you would use VLOOKUP to merge two datasets.
  • Write a formula to calculate the average of a dataset excluding outliers.
• Data Manipulation:
  • How would you clean and remove duplicates from a dataset in Excel?
  • Explain how you would use conditional formatting to highlight outliers in a sales dataset.
• Charting & Visualization:
  • Create a line chart to show the monthly growth in customer orders.
  • How would you use Excel to create a histogram to visualize product sales distribution?

3. Statistics & Probability Questions

Statistical knowledge is crucial for analyzing data and interpreting results. Expect questions on key concepts like probability, distributions, and hypothesis testing.

• Basic Probability:
  • If a product is purchased 20% of the time, what is the probability that it will be purchased exactly 3 times out of 10 trials?
  • What is the probability of two independent events occurring simultaneously?
• Descriptive Statistics:
  • Explain how you would calculate the mean, median, mode, and standard deviation of a dataset.
  • How would you handle a dataset that has extreme outliers?
• Hypothesis Testing:
  • What is a p-value, and how is it used in hypothesis testing?
  • Explain how you would set up and conduct an A/B test for a new feature on the Flipkart platform.
• Distributions:
  • What is the difference between a normal distribution and a skewed distribution?
  • Explain the significance of the Central Limit Theorem in statistical analysis.

4. Data Interpretation & Case Study Questions

You will often be given real-world data or scenarios and asked to derive insights or solve business problems.

• Case Study Example:
  • You’re provided with a dataset of customer orders, including product, quantity, and region. How would you identify the top-performing regions for a new product launch?
  • You’re tasked with analyzing customer churn data. What metrics would you use, and how would you present your findings?
• Business Impact Questions:
  • How would you analyze the impact of a new discount policy on sales revenue?
  • Given sales data over several months, how would you forecast future sales trends?
• Data Visualization:
  • How would you visualize customer purchase patterns over time using a line chart or a bar graph?
  • What type of visualization would you use to present category-wise sales data, and why?

5. Python (Optional)

Python is increasingly used in data analysis roles. If you mention Python in your resume, you might be asked to perform basic data manipulation using libraries like Pandas and NumPy.

• DataFrames:
  • Write a Python script to load a CSV file and calculate the total sales per product.
  • How would you filter a DataFrame to show only rows where the order value is greater than ₹1000?
• Data Manipulation:
  • Write a Python function to find missing values in a dataset and replace them with the column mean.
  • How would you merge two datasets in Python and remove duplicates?
• Visualization (Matplotlib, Seaborn):
  • Create a bar chart in Python to show monthly sales distribution.
  • How would you create a scatter plot to visualize the relationship between product price and quantity sold?

6. Problem-Solving and Analytical Thinking

You’ll be given a business scenario or dataset and asked to provide solutions or insights.

• Scenario-Based Questions:
  • Flipkart notices a decline in customer orders during weekends. How would you analyze this trend and propose a solution?
  • You’re given a dataset of customer browsing behavior. How would you identify patterns and suggest features to improve engagement?

7. Data Cleaning & Preprocessing

Questions related to how you clean and prepare data for analysis, ensuring accuracy and completeness.

• Handling Missing Data:
  • How would you handle missing values in a dataset? What are the different methods available, and when would you use them?
• Outlier Detection:
  • Explain how you would identify and handle outliers in a dataset before conducting analysis.
• Data Validation:
  • How would you validate that a dataset is accurate and complete before using it for analysis?

8. Optimization and Query Performance

Questions on optimizing queries for better performance, especially when working with large datasets.

• Optimization Techniques:
  • How would you optimize a SQL query that is running slow on a large dataset?
  • What indexing strategies would you use to improve query performance?

These questions are designed to test your technical proficiency, problem-solving ability, and analytical mindset required for a Data Analyst role at Flipkart. Make sure you are comfortable with SQL, data manipulation, statistics, and understanding business impact to excel in the technical rounds.

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