A recruiter reached out when I was doing my internship as a Data Scientist. One month later, I had my phone interview, which was straightforward about the basics of SQL and coding, requiring yes/no or one-word answers. I answered all questions correctly.

Within 2 hours, I received an invite for the next round, which was a coding interview.

I prepared intensely. As I will be working as a Data Scientist full-time next year, I felt confident. However, the questions were totally different from what others had mentioned: 3 Python questions and 3 SQL questions. I completed all the Python questions but could not solve all SQL questions due to time constraints (I completed 2 out of 3).

CoderPad's SQL interface is not good, and it was too difficult for me to run the codes because of a lack of interpretability. The SQL questions were of medium difficulty with a slight twist. My first question was a pretty straightforward percentage calculation, but I was getting an error without a clear explanation. I used advanced select statements and then CTEs, but kept getting an error, which was later resolved by multiplying by 1.0 at the end. I wasted 15 minutes on that single question.

The interview questions were difficult and different from normal questions. However, the CoderPad interface is very bad. I could have solved all the questions with a normal interface, but CoderPad is challenging to work on.

My advice would be to practice SQL questions on CoderPad as much as you can. Because it doesn't matter how much you know; it's all about how many questions you can complete in one hour.

I just finished the second round an hour ago and wanted to share my experience with everyone. I might get rejected due to not answering all the questions. But again, I wished they had a different interface and clearer question statements.

All the questions were doable.

All the best; you have an interview lined up with Facebook.

Loops, Percentage, Conditional Statements:

Python:

1. Replacing None values with the most recent elements (tricky test cases).
2. Average word counts (tricky test cases).
3. Unique strings in two lists (tricky test cases).

SQL:

• Percentage.
• HAVING clause with RANK statements.