iRageCapital

Role: Quant Research Intern

College: Not Specified

Interview Date: December 2022

Interview Type: Internship

Result: Rejected

Difficulty: Medium to Hard

Rounds: 2 rounds

Topics Asked: Data Structures, Algorithms, Statistics, Probability, Machine Learning, Aptitude, C++/Python

Experience:

This candidate interviewed for a Quant Research Intern position in December 2022, securing the interview through a referral. The preparation duration was one month, focusing on Data Structures, Algorithms, Statistics, Probability, and Machine Learning.

The interview process consisted of two main rounds:

• Round 1: Online Coding Interview (130 minutes, Easy Difficulty)
  • Two coding problems were asked.
  • Problem 1: Colorful Strings (Moderate) - Given an integer 'N', find the number of possible strings of length 'N' where each character is 'R', 'B', or 'G', with at least 'r' 'R's, 'b' 'B's, and 'g' 'G's.
  • Problem 2: Remove Edges - Given an undirected graph with 'N' vertices and 'M' edges. Edges are of type 1 (only traversable by 'A'), type 2 (only by 'B'), or type 3 (by both 'A' and 'B'). Determine the maximum number of edges that can be removed such that all nodes can still be traversed by both 'A' and 'B'.
• Round 2: Probability, Statistics, Aptitude, Machine Learning, and Coding Questions (60 minutes)
  • This round mostly covered general questions around probability and statistics.
  • Another coding problem was also part of this round.

The candidate was rejected because they did not prepare probability and statistics sufficiently and couldn't answer related questions properly.

Tips and Suggestions: The candidate advised having a strong understanding of probability and statistics, good experience with data modeling and machine learning, and a decent grasp of data structures and algorithms. They also emphasized not faking anything on the resume and having good, explainable projects.