Flipkart Data Scientist Interview Questions + Guide in 2025

Flipkart, India’s leading online marketplace, pioneers in providing a dynamic and inclusive shopping experience to millions of consumers. Known for its innovative approach and vast product selection, Flipkart generates terabytes of data daily, offering an exciting and challenging workspace for data enthusiasts.

Dive into our interview guide for a detailed walkthrough of the interview process along with commonly asked Flipkart data scientist interview questions to help you prepare better. Let’s get started!

The interview process usually depends on the role and seniority, however, you can expect the following on a Flipkart data scientist interview:

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the Flipkart Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process. You may also have an opportunity to discuss the role and company during this stage.

In some cases, the Flipkart data scientist hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. This interview stage may involve multiple aspects, including:

• Machine Learning Concepts: Questions revolving around ML models like logistic regression, supervised and unsupervised algorithms, boosting, and ensemble models.
• Mathematical Understanding: Deep dives into the mathematical aspects of machine learning models, including derivations and proofs.
• Probability and Statistics: Questions based on probability, hypothesis testing, and statistical models.
• Problem Solving: Case studies and real-world scenarios to gauge your problem-solving skills.

The technical virtual interviews will also include coding rounds, hands-on case studies, and presenting solutions or discussing past projects.

Onsite Interview Rounds

Following a successful technical screening, the next stage will involve onsite interview rounds, possibly at Flipkart’s Bangalore headquarters. You may experience:

• Presentation Round: An interactive presentation about your past work or a solved case study, lasting around 30 minutes.
• Technical Interviews: Multiple rounds focusing on in-depth machine learning concepts, coding exercises, and real-world problem-solving.
• Behavioral Interviews: These rounds focus on your decision-making skills, interpersonal communication, and fit within the company culture.

HR Round

The final step in Flipkart’s interview process includes an HR interview. This round will typically focus on your background, motivations, Notice period, and why you’re interested in working at Flipkart.

Typically, interviews at Flipkart vary by role and team, but commonly Data Scientist interviews follow a fairly standardized process across these question topics.

1. How would you set up an A/B test for multiple changes in a sign-up funnel?

A team wants to A/B test changes in a sign-up funnel, such as changing a button from red to blue and/or moving it from the top to the bottom of the page. How would you design this test?

2. Would you trust the results of an A/B test with 20 variants if one is significant?

Your manager ran an A/B test with 20 different variants and found one significant result. Would you suspect any issues with these results?

3. Why might the average number of comments per user decrease despite user growth?

A social media company sees a slow decrease in average comments per user from January to March in a new city, despite consistent user growth. What could be the reasons, and what metrics would you investigate?

4. What metrics would you use to evaluate the value of marketing channels for a B2B company?

Given all the marketing channels and their respective costs for a company selling B2B analytics dashboards, what metrics would you use to determine the value of each channel?

5. How would you locate a mouse in a 4x4 grid using the fewest scans?

You have a 4x4 grid with a mouse in one cell. You can scan subsets of cells to know if the mouse is within that subset. How would you find the mouse using the fewest number of scans?

6. Create a function find_bigrams to return a list of all bigrams in a sentence.

Write a function called find_bigrams that takes a sentence or paragraph of strings and returns a list of all its bigrams in order. A bigram is a pair of consecutive words.

7. Write a query to get the last transaction for each day from a table of bank transactions.

Given a table of bank transactions with columns id, transaction_value, and created_at, write a query to get the last transaction for each day. The output should include the id, datetime, and transaction amount, ordered by datetime.

8. Create a function find_change to find the minimum number of coins for a given amount.

Write a function find_change to find the minimum number of coins that make up the given amount of change cents. Assume we only have coins of value 1, 5, 10, and 25 cents.

9. Write a function to simulate drawing balls from a jar based on their counts.

Write a function to simulate drawing balls from a jar. The colors of the balls are stored in a list named jar, with corresponding counts of the balls stored in the same index in a list called n_balls.

10. Create a function calculate_rmse to compute the root mean squared error.

Write a function calculate_rmse to calculate the root mean squared error of a regression model. The function should take in two lists, one that represents the predictions y_pred and another with the target values y_true.

11. What’s the difference between Lasso and Ridge Regression?

Explain the key differences between Lasso and Ridge Regression, focusing on their regularization techniques and how they handle coefficients.

12. What kind of model did the co-worker develop for loan approval?

Identify the type of model used for determining loan approval based on customer inputs.

13. How does random forest generate the forest and why use it over logistic regression?

Describe the process by which a random forest algorithm generates its forest and explain the advantages of using it over logistic regression.

14. How would you interpret coefficients of logistic regression for categorical and boolean variables?

Explain the interpretation of logistic regression coefficients when dealing with categorical and boolean variables.

15. What is the expected number of good ads rated by different types of raters?

1. Suppose we have 100 raters each rating one ad independently. What’s the expected number of good ads?
2. Now suppose we have 1 rater rating 100 ads. What’s the expected number of good ads?
3. Suppose we have 1 ad, rated as bad. What’s the probability the rater was lazy?

16. Write a function to simulate coin tosses with a given probability of heads.

Create a function that takes the number of tosses and the probability of heads as input and returns a list of randomly generated results (‘H’ for heads, ’T’ for tails).

Example 1:

tosses = 5
probability_of_heads = 0.6

Output:

coin_toss(tosses, probability_of_heads) -> ['H', 'T', 'H', 'H', 'T']

Example 2:

tosses = 3
probability_of_heads = 0.2

Output:

coin_toss(tosses, probability_of_heads) -> ['T', 'T', 'T']

17. Write a function to calculate the sample variance of a list of integers.

Create a function that takes a list of integers and returns the sample variance, rounded to 2 decimal places.

Example:

test_list = [6, 7, 3, 9, 10, 15]

Output:

get_variance(test_list) -> 13.89

18. What is the probability of rolling at least one 3 with dice?

1. What’s the probability of rolling at least one 3 with 2 dice?
2. What’s the probability of rolling at least one 3 given (N) dice?

19. What is the probability of finding an item on Amazon’s website given its availability in warehouses?

Given that the probability of item X being available at warehouse A is 0.6 and at warehouse B is 0.8, what is the probability that item X would be found on Amazon’s website?

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your Flipkart data scientist interview include:

• Understand and Explain Your Work: Be ready to thoroughly discuss your past projects. Expect to dive deep into technical details and mathematical proofs, especially focusing on ML models and optimization problems.
• Highlight Mathematical Proficiency: Emphasize your understanding of mathematical concepts behind machine learning algorithms. Practice derivations and proofs for topics like logistic regression and ensemble methods.
• Be Prepared for Real-World Applications: Brush up on solving case studies and practical problem-solving scenarios. Flipkart’s interviews often involve applying ML techniques to business problems, so being contextually sharp will be beneficial.

What is the average salary for a Data Scientist at Flipkart?

According to Glassdoor, Data Scientist at Flipkart earn between $134K to $183K per year, with an average of $156K per year.

What skills are required for a Data Scientist position at Flipkart?

To work as a Data Scientist at Flipkart, you need a deep understanding of machine learning algorithms, statistical models, and proficiency in programming languages like Python or R. Strong analytical and problem-solving skills, as well as experience with supervised and unsupervised learning algorithms, are also important.

What kind of work does a Data Scientist at Flipkart do?

A Data Scientist at Flipkart develops and implements machine learning or statistical models for various business and product-related projects. The role involves collaboration with engineering and product teams, extracting insights from data, and active participation in research and learning new technologies.

What is the company culture like at Flipkart?

Flipkart has a dynamic and inclusive company culture that values learning and innovation. Employees are encouraged to take ownership of their work, experiment, and grow. The workplace fosters collaboration and aims to create a significant impact on India’s online shopping landscape.

The Flipkart Data Scientist role demands a unique blend of technical expertise, problem-solving skills, and collaborative spirit. If you excel in supervised and unsupervised algorithms, have hands-on experience with diverse Machine Learning models, and are ready to tackle real-world problems, this opportunity at Flipkart could be an ideal fit. The interview process is rigorous, with multiple rounds focusing on coding, deep data science knowledge, mathematics, and real-world case studies.

For a deeper dive into Flipkart’s interview process, check out our detailed Flipkart Interview Guide, where we cover a variety of interview questions and provide valuable insights to help you prepare. Explore other roles and their interview guides as well to understand the broader scope of opportunities at Flipkart.

Good luck with your interview!