Swiggy private limited

Swiggy private limited Interview Experience

Rejection

Swiggy private limited Interview Experience for Fresher Associate Data Scientist, Dec 2025

Role

Associate Data Scientist

Experience

Fresher

Platform

Website

Prep Duration

15 days

Eligibility / Offer Details

7 CGPA, (Salary package: 9 LPA)

Branch

Computer Science Engineering

Total Rounds

2 Rounds

Application Experience

I applied through Swiggy’s career portal and received a call from the recruiter after 10 days. We discussed salary expectations and location preferences, and she explained the interview process. The initial interview date was postponed, and after a week, I received an email with the updated schedule. All the interviews were eventually scheduled on a single day.

Preparation

Topics Prepared: Data Structures, SQL, Python, Machine Learning, Algorithms, and case-studies based on Swiggy

Preparation Tips

Tip 1: DSA questions are a must, so be prepared—even for data-related roles. Tip 2: Strong knowledge of SQL joins and real-time projects is a plus. Tip 3: Machine Learning and Deep Learning concepts should be understood in depth.

Resume Tips

Tip 1: Keep at least two relevant projects if you don’t have work experience. Tip 2: Mention only the skills you are genuinely familiar with.

Interview Rounds (2)

Detailed breakdown of each evaluation round, questions asked, and candidate approaches.

Round 1

Round 1 — Face to Face

45 minutesMediumCleared

In the first round, a coding problem and some simple SQL questions were asked, mainly focused on data retrieval and joins. This was followed by questions on Python basics and a discussion of the projects mentioned in my resume.

Problems & Questions Asked (1)

Integer To Roman Numeral

Problem Statement

Given an integer ‘N’, the task is to find its corresponding Roman numeral. Roman numerals are represented by seven different symbols: I, V, X, L, C, D and M. Symbol Value I 1 V 5 X 10 L 50 C 100 D 500 M 1000 Example : 2 is written as II in the roman numeral, just two one’s added together. 12 is written as XII, which is simply X(ten) + II(one+one). The number 27 is written as XXVII, which is XX + V + II. Roman numerals are usually written largest to smallest from left to right. However, the numeral for four is not IIII. Instead, the number four is written as IV. Because the one is before the five we subtract it making four. The same principle applies to the number nine, which is written as IX. There are six instances where subtraction is used: I can be placed before V (5) and X (10) to make 4 and 9. X can be placed before L (50) and C (100) to make 40 and 90. C can be placed before D (500) and M (1000) to make 400 and 900. Input Format : The first line of input contains an integer ‘T’ denoting the number of test cases. Then the test cases follow. The only line of each test case contains an integer ‘N’. Output Format : For each test case, the only line of output prints the corresponding roman numeral for the given integer ‘N’. Note: You do not need to print anything, it has already been taken care of. Just implement the given function. Constraints: 1 <= T <= 10^2 1 <= N <= 4*10^3 - 1 Time Limit : 1 sec

Candidate Approach

Tip 1: Start from explanation of your approach then clarify before you code. Tip 2: Mention time complexity and about data structures used in your code properly to show better understanding.

Round 2

Round 2 — Face to Face

45 minutesEasyCleared

This was an ML fundamentals and statistics round. It took place two hours after the first round, and only candidates who cleared Round 1 were eligible for it. Several problem-solving and conceptual questions were asked, mainly focused on machine learning, as well as on the deep learning models and algorithms used in my projects.

Problems & Questions Asked (2)

Machine Learning

Problem Statement

Explain pros and cons of neural networks in ML. (Learn) Explain the benefits of random forest with use cases. (Learn) What are overfitting and underfitting, and what solutions did you use to overcome them? (Learn) What scenarios require probability calibration for classification models?

Candidate Approach

Tip 1: Try to explain concepts very smoothly and clearly. Tip 2: Must give examples wherever required.

Selection Perspective

Problem Statement

I was rejected in the second round. I was not informed directly about the rejection, but I later noticed that the portal status had been updated to show that my application was dropped. Both rounds went well, and the interviewers seemed impressed.

Key Preparation Tips

Prepare DSA thoroughly.

Practice aptitude and puzzle-based questions.

Have at least two good projects on your resume.

Be prepared to explain your projects clearly.

Practice coding problems involving Arrays, Binary Search, DP and Recursion.

Prepare common HR questions such as Tell me about yourself and Who is your role model?

Candidate Approach