Basic Information
- Company Name: Quadeye
- Name: N V Navaneeth Rajesh
- Role: Quant Intern
- Location: Gurugram
Please elaborate on your internship role and/or any projects that you did?
The internship mainly consisted of a single large group project. Working as a group of 5, we had to make a pipeline which good perform preprocessing, data cleaning and applying various ML models to extract insights. Basically on providing a source of data, the final output would be the PnL over a year or so along with other statistics.
Please describe the selection process in detail (tests + interviews)?
There was a test with about 10 questions for the Hong Kong profile. The India profile selections were mostly based on the scholarship test results. Around 6 interviews totally. Only 2-3 questions per interview, focus was mainly on brainteasers, probability and mental math.
What was your preparation strategy for Quant roles (trading and/or software)?
I followed all the usual advice and resources, Green Book, Brainstellar and 50 challenging problems in probability for aptitude. Zetamac for mental math and Leetcode for DSA. My focus was primarily on trading roles, so just basic dsa and a good knowledge of python was adequate. I practiced each of the aptitude resources a couple times, that helps to build your intuition, as for mental math, apart from Optiver no firm gives a lot of weightage to it but it is a useful skill to have.
What were the working hours like?
The working hours were pretty long, 9 to 8 ish from Monday to Friday. Weekends are off but you might have to do a bit of work towards the deadline.
How would you describe the structure, work culture and work-life balance of the company?
Quant is notorious for poor work-life balance. That being said, weekends give you a lot of time for hobbies or sightseeing. With a good schedule, you should be able to manage. As an intern, we weren’t really exposed much to the company work culture, but among ourselves, we were pretty helpful and cooperation was encouraged.
A lot of Quant firms claim they don’t have silos, and use this as a USP. How true is this for the company you interned at?
Atleast in Quadeye, although there are separate teams for software and quant and multiple teams within quant, there is a ton of communication accross teams. Traders and devs have constant communication to report and fix bugs asap.
Was there any evaluation criteria followed by the company, if yes could you elaborate?
The evaluation criteria wasn’t revealed, but essentially it was not dependent on the results you bring but rather on how well you work. What sort of insights or approaches do you have and how well can you communicate them.
How did the internship influence your career interests?
The internship did reaffirm that a career in quant could be on the cards and is an exciting industry to be a part of.
How would you rate your overall internship experience?
8.5/10 Much better than what was expected based on reviews from our seniors.
Any myths or unknown facts you would like to bust/reveal? Feel free to add in any comments you have.
There is a myth that traders don’t need to know coding and software devs don’t need to know anything about trading. This isn’t true, for the most part, traders do need to know quite a bit of coding to implement their algorithms and execute them and for sw devs, it is better to know a bit about trading as it comes in handy when you need to make tools for traders.
Probability, stats and systems are probably the most important courses for quant, if you do have an interest in these, then you could consider a career in quant.
One piece of advice for someone preparing for similar roles.
Just be consistent in your preparation and efforts, make sure to keep switching topics when preparing so that you stay in touch with everything.