Feel free to post questions below, and I'll try to address them as well as I can 
I am a Quant C++ Dev in NYC, working closely with a large quant team and loving it (mostly). AMA
- Thread starter Pavlos Sakoglou
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Hi Michelle! I graduated with a business admin degree (mostly soft skills) and slowly transitioned to math/tech by taking courses and certificates and self-studying. Similarly, I enrolled in Quantnet's C++ certificates which gave me the confidence to attempt software engineering. A few years later, I graduated with my master's in mathematics, with some financial engineering and CS background, and with strong C++ skills. I got my first job at a bank, and after a year, I moved up to a senior role as a trading systems developer for another three years. Recently I switched to my current role.
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You say you Quantnet's C++ courses gave you confidence, and then years later you had strong skills. How long did it take to transition from Quantnet's C++ courses to 'strong C++ skills,' or hire-able skills, and how well do Quantnet's courses alone prepare one for a real job?
*Edit: I just realized you are the same author as the 'how Quantnet C++ courses got me a job on Wall Street' pinned post. Reading through those responses gives me a decent idea of what your repose would be.
I'll leave the original question unedited above, but I'd also like to know how well these courses prepare someone for a non-software dev role. Trading or research. I've read different colleges earnings reports, Baruch's says that most of their graduates spend >50% (with many >70%) of their time coding. But I'm not sure what that looks like in the different roles.
Are these courses plus a decent amount of practice enough for a trader/researcher to get the bones and then be able to poke around to test some stuff, then hand it off to the software side and for them to optimize? (Obviously after additional MFE type training to know what they should be using the skills to do). Also, is that description of passing it along after tinkering for proof of concept accurate?
*Edit: I just realized you are the same author as the 'how Quantnet C++ courses got me a job on Wall Street' pinned post. Reading through those responses gives me a decent idea of what your repose would be.
I'll leave the original question unedited above, but I'd also like to know how well these courses prepare someone for a non-software dev role. Trading or research. I've read different colleges earnings reports, Baruch's says that most of their graduates spend >50% (with many >70%) of their time coding. But I'm not sure what that looks like in the different roles.
Are these courses plus a decent amount of practice enough for a trader/researcher to get the bones and then be able to poke around to test some stuff, then hand it off to the software side and for them to optimize? (Obviously after additional MFE type training to know what they should be using the skills to do). Also, is that description of passing it along after tinkering for proof of concept accurate?
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Hi Mike! QN's courses will teach you programming techniques and C++ features, which are essential and that I (and a lot of the quants I work with) encounter at the job daily. As far as C++ is concerned, you will get plenty of value. Many of these concepts come up during interviews as well.
It took me roughly 5-6 months of additional full-time education and software dev training after I finished QN's advanced C++ course and before I got hired -- but that really depends on one's background.
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Thanks.
What does the coding look like in non-dev quant roles (i.e. trading, research)? It is said that they code the majority of their time too.
Also, I have heard that those teams typically just get proof of concept in Python or something simpler, then hand it off to developers to get optimized. Is this accurate?
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Hi Pavlos!
I recall reading your article multiple times on how the QuantNet courses got you a first job on Wall Street. Quite an interesting read.
1) Out of curiosity, what did you do in terms of preparation after completing the advanced C++ course?
2) I recall you mentioning that the 'Advanced' course [was] the most challenging course you ever took. It seems like we completed the first one in about the same time (and with 'Distinction'), but you took 4.5 months (and 5-6ish hours per day) to complete the second one. Would you say that timeline is a fair time to complete the course or was it due to personal research you did on the side?
I recall reading your article multiple times on how the QuantNet courses got you a first job on Wall Street. Quite an interesting read.
1) Out of curiosity, what did you do in terms of preparation after completing the advanced C++ course?
2) I recall you mentioning that the 'Advanced' course [was] the most challenging course you ever took. It seems like we completed the first one in about the same time (and with 'Distinction'), but you took 4.5 months (and 5-6ish hours per day) to complete the second one. Would you say that timeline is a fair time to complete the course or was it due to personal research you did on the side?
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Hi, the cost of living is...BAD. Rent and groceries is much higher, but entertainment is pretty much as it was, maybe a small increase.
Crypto scene feels like it's laying low right now, but there are a lot of job openings for Fintech/etrading firms and startups. Big banks are steady as always, also not much risk-taking.
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It really depends on the role, most quants are very strong with C++ and they handle the development themselves. Python is used a lot, for prototyping, also for testing, for components that are not performance-critical, and for task automation.
Daniel Duffy
C++ author, trainer
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Pavlos,
which topics in the course were most/least
1. fun
2. useful
3. difficult
which topics in the course were most/least
1. fun
2. useful
3. difficult
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It really depends on the team, a company may decide the need a pure dev team to write code while quants do the math, but it seems more likely to find teams where quants write most of the production code.
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1. I spend time on algorithms and data structures from both theoretical CS and practice problems perspectives, I installed Linux and and learned about build systems and OS optimization techniques, and did a lot of interview practice (mock interviews, interview questions, etc).
2. I took the advanced class during summer break and I spend a lot of extra time making sure I learn everything about every exercise. If my goal was to just complete the course and get some basic knowledge, it would probably take me much less, maybe half the time.
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What were the best interview prep materials you used? Was it the typical stuff like leet code or anything else more targeted towards our particular field?
Did you use any outside textbook resources while taking the advanced course or just spent the extra time re-studying the lectures and leveraging google?
Did you use any outside textbook resources while taking the advanced course or just spent the extra time re-studying the lectures and leveraging google?
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I try to wake up around 7:30am, do some personal work and catch up with emails, then take the subway to work around 8:20am.
At work, I have morning meetings starting 9am, I then grab some quick breakfast and coffee from the pantry and get on with my work day. I spend most of my time supporting quants with development and making sure our pipelines are up and running. I try to get involved with at least one code review per day, and I spend an hour or two coding for my current project. I'd occasionally take some internal course from the company portal or watch Cppcon videos on YouTube. Depending on the day, sometimes I have to drop everything and work on an urgent issue that blocks development. I almost never eat lunch on my desk, usually I step out for at least 20 minutes, but not more than 40.
I get home typically around 5:45-6pm and spend my evening either going for a light workout, cooking, going out, or movie night. Twice a week I work from home, which is a treat cause I can wake up later and stay comfortable.
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As a student, at the time I'd say:
Most
1. Fun: lambda programming and the final projects
2. Useful: templates and meta programming
3. Difficult: Design Patterns with threads
Least:
1. Fun: Type traits and decltype
2. Useful: Quizzes
3. Difficult: STL
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I was prepping for software dev jobs, so I focused on leet code and going through the CLRS Introduction to Algorithms book (graphs, trees, data selection, sets, etc.). I tried to implement all main data structures and their algos, I was only using Linux and the terminal, I became fluent with git, and tried to work on projects to talk about during interviews.
During the advanced course I'd search a lot and find other resources so I could grasp the concepts better -- cppreference and YouTube were my top places to go.
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Thank you Pavlos for coming back and sharing your experience. We appreciate you, sir.
I'm featuring this on the homepage so this can get more attention.
Now, what would you do differently if you went back and were in the positions of many members here, planning to get a finance job? How would you prepare knowing what you know now.
I'm featuring this on the homepage so this can get more attention.
Now, what would you do differently if you went back and were in the positions of many members here, planning to get a finance job? How would you prepare knowing what you know now.
