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Canada Quant Jobs

Hi all, I was wondering how much Toronto quants at top Canadian investment banks make (TD, RBC, SCOTIA, CIBC...)? Is the pay comparable to NY quants, or is the pay usually significantly lower? From what I have found on the internet, quants in Toronto make about 80K a year; do you know whether or not this is accurate?
 
Hi all, I was wondering how much Toronto quants at top Canadian investment banks make (TD, RBC, SCOTIA, CIBC...)? Is the pay comparable to NY quants, or is the pay usually significantly lower? From what I have found on the internet, quants in Toronto make about 80K a year; do you know whether or not this is accurate?
much (significantly) lower. but not as low as 80k lol...

associate 100-200, VP 200-300, D 300-450ish(>)
 
Are these salaries for fresh MFE graduates?
And what about the working hours? Are they comparable to IB analysts (80+ hour work weeks) or more like a 9-5?
Yes they are. But fresh grads are mostly associates.

It is 8-6. The work can be very stressful.
 
how can you have stressful work in canada?
For some desks, most of the the notes are issued in US. There might be billions of $ tie to your model and you can’t afford to fuck up... also these roles are very limited in Canada as well, if fucked up then I might be forced to look in US lol 😂 and life is too comfortable in Canada I have no intention to move
 
much (significantly) lower. but not as low as 80k lol...

associate 100-200, VP 200-300, D 300-450ish(>)

How competitive are these positions? I work in the back-office in credit risk (PD/LGD modelling) at one of the big banks in Toronto but was looking into moving into the front-office in a quant role. My background is in engineering (BASc and MASc) and did a master's thesis in numerical PDE so I really enjoy quantitative modelling. It seems like most of the quants at my bank are split between PhD's, STEM master's, and MFE and I only see maybe 1-2 postings at my bank for front-office quant positions a year. I'm not sure if it's worthwhile to continue with my self-study plan to prepare for applying to these positions (study stochastic calculus, developing a pricing library in C++) or to move over to data science positions which can also be quite lucrative, especially since there's only a handful of these positions available each year. There's actually a group at my bank adjacent to the pricing model development team that does pure ML and they also seem to be getting into pricing and they just hired a huge team. It seems like the bank is now focusing more on ML methods than traditional pricing techniques. A bunch of the pension funds also seem to be developing their machine learning teams.
 
How competitive are these positions? I work in the back-office in credit risk (PD/LGD modelling) at one of the big banks in Toronto but was looking into moving into the front-office in a quant role. My background is in engineering (BASc and MASc) and did a master's thesis in numerical PDE so I really enjoy quantitative modelling. It seems like most of the quants at my bank are split between PhD's, STEM master's, and MFE and I only see maybe 1-2 postings at my bank for front-office quant positions a year. I'm not sure if it's worthwhile to continue with my self-study plan to prepare for applying to these positions (study stochastic calculus, developing a pricing library in C++) or to move over to data science positions which can also be quite lucrative, especially since there's only a handful of these positions available each year. There's actually a group at my bank adjacent to the pricing model development team that does pure ML and they also seem to be getting into pricing and they just hired a huge team. It seems like the bank is now focusing more on ML methods than traditional pricing techniques. A bunch of the pension funds also seem to be developing their machine learning teams.
Quite competitive but do-able.

If you don't mind relocate then it is much easier to just look in US markets. Canadian banks FO roles are still focusing on pricing derivatives. For those you mentioned, I don't think they know what the heck they are doing when it comes to data science lol...

I worked for a big bank before (GS/MS tier) as a strat. You can find how data science is actually being used properly in this thread: What does eTrading do in a bank? (eFX, eRates, etc)

Also you don't need to hard study on stochastic calculus. You just need to know 1-6 chapters of Steve Shrev's book and the rest you will learn on the job. If you want to have an edge then simply read log-contract approach, local vol construction, multi-curve discounting and SABR. My advice is to become insanely good in C++ or C#(if u want to work for bmo)...
 
Quite competitive but do-able.

If you don't mind relocate then it is much easier to just look in US markets. Canadian banks FO roles are still focusing on pricing derivatives. For those you mentioned, I don't think they know what the heck they are doing when it comes to data science lol...

I worked for a big bank before (GS/MS tier) as a strat. You can find how data science is actually being used properly in this thread: What does eTrading do in a bank? (eFX, eRates, etc)

Also you don't need to hard study on stochastic calculus. You just need to know 1-6 chapters of Steve Shrev's book and the rest you will learn on the job. If you want to have an edge then simply read log-contract approach, local vol construction, multi-curve discounting and SABR. My advice is to become insanely good in C++ or C#(if u want to work for bmo)...
May I ask about your educational background?
 
Quite competitive but do-able.

If you don't mind relocate then it is much easier to just look in US markets. Canadian banks FO roles are still focusing on pricing derivatives. For those you mentioned, I don't think they know what the heck they are doing when it comes to data science lol...

I worked for a big bank before (GS/MS tier) as a strat. You can find how data science is actually being used properly in this thread: What does eTrading do in a bank? (eFX, eRates, etc)

Also you don't need to hard study on stochastic calculus. You just need to know 1-6 chapters of Steve Shrev's book and the rest you will learn on the job. If you want to have an edge then simply read log-contract approach, local vol construction, multi-curve discounting and SABR. My advice is to become insanely good in C++ or C#(if u want to work for bmo)...
Thanks, that's super helpful. I may reach out in the future for some more advice. Yeah, my plan was to read through Shreve and then develop a C++ pricing engine. I know BMO primarily does C# but C++ seems to be the most prevalent/versatile. When hiring quants are you exclusively looking for PhD? Also, what do you specifically look for on a resume or in an interview.
 
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Thanks, that's super helpful. I may reach out in the future for some more advice. Yeah, my plan was to read through Shreve and then develop a C++ pricing engine. I know BMO primarily does C# but C++ seems to be the most prevalent/versatile. When hiring quants are you exclusively looking for PhD? At my bank that doesn't seem to be the case but some jobs seem to ask for it.
Hmm it depends. I can't speak for others but for me probably a master in a quantitative discipline (may it be CS/Eningeering/Math/etc) from a targetted school is good enough. The rest is to pass the interview.

I would recommend the green book and leet coding for new grad. Learning stoch calc is good but not as important. That being said, if you already master the interview Qs. Then sure, go learn those.
 
Bacheor in Math + MFE. Learn my coding through internships and leet code :)
And as an advice, would you encourage me to continue programming mainly in python or should I pick up C++ skills? I'll be starting my undergrad in fall 2021 and I currently have decent knowledge in python (data science/ML). Am I doing the right thing, or would I be better off learning C++?
 
And as an advice, would you encourage me to continue programming mainly in python or should I pick up C++ skills? I'll be starting my undergrad in fall 2021 and I currently have decent knowledge in python (data science/ML). Am I doing the right thing, or would I be better off learning C++?
oh lol... u r just in your undergrad... well... then i would say learn as much as you can. Enjoy it. Isn't it too early to anchor to a career which might not be a thing when you graduate? if you like math then learn math. There are lots of career you can choose. Data science/quants/software engineers.

since you are still young, how about learn both? there is only upside for knowing more.
 
oh lol... u r just in your undergrad... well... then i would say learn as much as you can. Enjoy it. Isn't it too early to anchor to a career which might not be a thing when you graduate? if you like math then learn math. There are lots of career you can choose. Data science/quants/software engineers.

since you are still young, how about learn both? there is only upside for knowing more.
Well I'm open to several other options mainly in actuarial science/ML/Data science. One last thing I want to ask; on average, how long does it take a quant to reach VP and MD levels? Thanks in advance man! You were very helpful.
 
Well I'm open to several other options mainly in actuarial science/ML/Data science. One last thing I want to ask; on average, how long does it take a quant to reach VP and MD levels? Thanks in advance man! You were very helpful.
There is no concrete answer. But VP is gurantee max 5 years as associate. Exactly when depends on how good you are.

D/ED is not guarantee.. some folks might be capped at VP.

MD is very difficult.
 
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