From consulting to quant career advice

[physguy]

Hi everyone,

I am a physicist with an MSc in Theoretical Physics from european university (not UK). I work for a consulting firm for almost a year now. My role is in Risk consulting, and I have worked in 2-3 projects already, mainly in quantitative projects in Risk.

Before starting my current job, my goal was to be a quant in a bank/hedge fund, either middle office (MO) risk management or as a front office (FO) quant trader (I wanted front office more, but I was not sure if I could land a job there without PhD). However, having started the job in this area (all of the projects were in MO risk in banking), I have realized that....MO risk management is boring to me. The thing is , I really love math, and that's why I was considering a quant career. But in all of the projects I have personally worked, the projects involved very simple math/coding and they were mainly about implementing regulations. Keep in mind that in all of the projects I was working side by side with bank quants and it seemed that this is what they are also doing in their regular day to day jobs.

So after this experience, I came to reconsider a bit. Now, I am thinking that I would not like to spend my entire career in middle office risk management (nothing wrong with this of course, it's just not for me from what I' ve seen) and honestly I would definitely prefer to have a consulting career over this. FO is still the dream for me. So after a lot of overthinking, I have some questions about that I would ask you:

1) Is my experience useful or am I misled? After all, I have not worked as MO quant, I just have consulting experience in this field. Maybe they hire consultants only for the boring projects, and their day to day work is more interesting/has more math or coding? What's the truth? All the projects I worked were in credit risk (model validation and model development).

2) The way I see it and in a very rough way, there are only two quant categories. FO quant trader/algo/HFT and MO risk? Is there anything else?

3) As I said I have worked only in credit risk. Which division of MO has the most quantitative work (math/coding)? Credit Risk, Market Risk, Liquidity Risk, Treasury, something else?

4) Which team do you believe has the most quantitative work? Model validation, Model development, something else?


5) As I said above my end-goal is to somehow go into FO role? Is this highly unlikely without a PhD (highly unlikely means <5% probability)? I am not really into spending 1-2 years on an MFE, I do not want to spend the money or the time, at least not for now. I am really motivated and certain that I can learn a lot on my own. But without PhD or MFE certificate, do I even stand a chance?

6) If I do not land a job in FO immediately (most likely outcome I would say), is there any point in going MO risk with the goal of transitioning to FO? Finding a MO role seems realistic to me, since I have seen people in the past transitioning from risk consulting to such roles. If this seems realistic, which roles/teams/division should I chase? Also which banks (G-Sibs perhaps?)?

I would really appreciate it if you answer any of these questions

 

[ParticlePhynance]

Hi,

I also started in MO risk quants at a bank and can confirm: the job is pretty boring and removed from markets (same, or even more, for model val).

For 2) no, there are many more quant categories. Sell-side: FO quants (modelling/library, strat, algo), Risk (ccr, mkt risk, model val). Buy-side: quant dev, systematic researcher. Pay is more or less: buy side systematic > sell-side algo > sell-side strat/modelling = buy-side dev > ccr/mkt risk > model val

As for getting a sell side fo quant role, you don't need a phd but you need a master from a target school. Agree that you can learn the material on your own, but you won't get interviews without a top msc/phd in your cv.

Yes I can see why you don't want to get an MFE but then again a recruiter might say why should I hire you when there are tens of qualified people from top MFEs? There are hundreds of applications of each of these jobs and you have to want it more than the others (and in some ways show from your cv that you do).

MO risk to FO quant is doable if you are young (analyst/associate level) but is not guaranteed and would take a lot of effort. I managed to do it, but I was still in my first year and took me like 40 coffee chats with people from the bank to pull it off (and if it had not worked out within my second year I also had an offer for a top MFE and I would have gone there, because the more you stay in risk, the harder it gets to move out).

Personally I would apply for a top MFE: you will get all the interviews you want after that and will repay the investment pretty soon. I know a pretty smart physics phd who told me he couldn't get a single interview from london HFs before his masters. At the end of the master he had 13 offers from top banks/HFs. Also self studying the stuff you need to pass FO quant interviews will require all your free time for 1 year, so not sure it's much less effort than doing a master.

 

[physguy]

Thank you very much for your response. Really insightful!

Do you think that age plays a role in the hiring processes? I am already 27, so maybe that is a prohibitive factor too (since most people get a position right after MSc/PhD)?

Also, if I am not mistaken, you are in London, is that right? Since I am in Europe, are all positions located in London (so the closer I am there, the better for a possible change)?

 

[ParticlePhynance]

Happy to help. No age is not a factor at all for quant finance: in my bank we have algo VPs in their 40s. The physics phd guy I was mentioning above was 30 when he entered his PhD.

Most positions are indeed in London. There are some in paris (especially BofA, GS and MS) and in zurich (for UBS / CS). But agree that London is the easiest.

You're 27: you are still young and got some relevant experience. I would just spend the summer doing interview prep and then apply for a good MSc in autumn and use that to pivot into a good role.