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.
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.
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.



Symbol Value
I 1
V 5
X 10
L 50
C 100
D 500
M 1000
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.
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.
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.
Tip 1: Try to explain concepts very smoothly and clearly.
Tip 2: Must give examples wherever required.

Here's your problem of the day
Solving this problem will increase your chance to get selected in this company
What does dict.keys() return?