by Brian DeChesare Comments (23)

The Full Guide to Quant Funds: Careers, Salaries, Recruiting, Exits, and More

Quant Funds

If you go by online commentary, quant funds, also known as “quantitative hedge funds” or “quant hedge funds,” have taken over the world.

Rather than relying on antiquated concepts like fundamental analysis and human discretion, quant funds use data, statistical models, algorithms, and automated systems to trade.

Some quant funds, such as Renaissance Technologies, have performed amazingly well, with its Medallion Fund generating 66% annualized returns between 1988 and 2018.

But pointing to Renaissance as evidence of quant investing being “the best” is a bit like pointing to Warren Buffett as evidence of value investing being “the best.”

Yes, either strategy can perform well, but there’s only one Warren Buffett – and only one Renaissance.

Industry-wide performance is a mixed bag, and while quant funds offer plenty of benefits, such as extremely high starting compensation, I believe they’re a bit overhyped.

But before digging into the performance and salary levels, let’s start with the fundamentals of quant funds:

What is a “Quant Fund”?

Quant Fund Definition: A quant fund is a hedge fund that uses statistical techniques, mathematical modeling, and automated algorithms, rather than fundamental analysis and human judgment, to make investment decisions and execute trades.

Like all hedge funds, quant funds raise capital from institutional and accredited investors and invest it in liquid, publicly-traded assets to outperform the overall market.

Quant funds can be single-manager or multi-manager, and the trade-offs are similar: SM funds are more like “practices,” while MM funds operate more like corporations.

So, the key distinction is the investment analysis.

A hedge fund Analyst at a long/short equity fund might spend a lot of time reading annual and interim reports, speaking with management teams, conducting due diligence, and building traditional financial models.

But at a quant fund, Analysts spend their time devising statistical criteria to make investment decisions and testing those criteria with backtests before using them in live markets.

For example, a Quant Researcher might spend the day thinking about this type of question:

“Here are 200 possible conditions that might result in the stock price of Company X rising. Let’s test the statistical significance of these conditions and use them to predict the direction of Company X’s stock price.”

The researcher would then brainstorm a list of these conditions based on other strategies, academic papers, and analysis of internal data:

  • Over the past 10 years, whenever Company Y’s stock rose by 10%, Company X declined by 5%; there’s a 65% correlation between the two.
  • Over the past 5 years, whenever the trading volume of Company X exceeded A, its stock price increased by X% on average; there’s a 50% correlation between the two.
  • In the past year, whenever oil exceeded $Z per barrel, Company X declined by Y% on average; there’s a 70% correlation between the two.

The Quant Researcher would then use these findings to develop a mathematical model for Company X’s stock price.

The Trader would develop strategies to get the best price on each trade, and the Developer would implement the investment strategy and trading execution in code.

Wait, But What is a “Quant”?

Banks and other finance firms have started labeling every position “quant,” so it has become a nebulous term.

It could mean anything from a middle-office role at a bank to an algorithmic trader at a large bank to a hedge fund professional who owns their P&L.

To make things even more confusing, many hedge funds also employ “quants” for risk management or price modeling.

If you work in risk management, you are doing something “quantitative,” but it’s not quite the same as coming up with ideas that could generate trading profits.

This article will focus on quant research roles at hedge funds, where the main job is to devise investment strategies.

The Quant Fund Team: Researchers, Traders, Developers, and Everyone Else

At most quant funds, the main categories of junior-level employees are:

  1. Quant Researchers or Quant Analysts: They create statistical models by reviewing academic research, brainstorming ideas, and backtesting new strategies. You’ll see many statisticians, physicists, and mathematicians in these roles, and quite a few have Ph.D.’s – though an advanced degree is not necessarily required.
  2. Quant Traders: Traders execute the researchers’ ideas, but at quant funds, they also code and create automated systems to make trades. The difference is that they focus on the efficiency of this trading activity rather than creating strategies in the first place.
  3. Quant Developers or Software Engineers: They develop data access and analytical tools, and they have to understand not the software and hardware but also markets and trading strategies. They must write clean, extensible, and robust code because the algorithms change all the time.
  4. Business Development / Operations / Compliance: Professionals in these areas work on non-investment tasks for the fund, such as complying with regulatory frameworks, figuring out taxes and fees, and improving efficiency.

The names differ slightly depending on the firm; you can see Jane Street’s version here or Citadel’s version here.

Above these levels, there are the Portfolio Managers (PMs) and senior executives (if the firm is big enough).

At quant funds, PMs are also in charge of final investment decisions, risk management, investment logistics, marketing, and fundraising.

The difference is that rather than judging individual trade ideas generated by the Analysts, they’ll review automated strategies and decide which ones to implement based on backtest results and smaller tests run in the live markets.

For example, if the PM manages a $100 million portfolio, they might allocate $20 million to Strategy #1 and $10 million to Strategy #2 because of concerns that Strategy #2 might create too much portfolio-wide risk.

Why Do Quant Funds Need So Many People? Isn’t the Trading Automated?

The short answer is that no strategy works forever.

Market conditions change over time, and strategies become less effective as more firms use them.

Back in 1990 or 2000, you might have been able to build a trading strategy and “set it and forget it,” but the past few decades have turned that into a pipe dream.

So, the Researchers, Traders, and Developers constantly tweak the models and code to adjust the firm’s strategies.

And after a certain point, simple tweaks stop working, so they’ll need to generate completely new ideas.

As the “half-lives” for these new ideas decrease, even larger teams and more work are required.

The Path to Portfolio Manager (PM)

Once you pass the 4-5-year mark, your compensation flattens out, so you need to win a promotion to Portfolio Manager if you want to earn more.

As with all hedge funds, you need to show strong P&L results that you can claim directly.

But if you’re researching strategies and building statistical models, it isn’t easy to take 100% credit for anything that happens – especially if you’re in a large team.

There’s nothing “wrong” with staying in a Quant Researcher position rather than advancing to PM, as you’ll still earn a ton of money if you perform well.

But your career will be less stable, and your compensation will reach an admittedly high ceiling.

The best way to advance to a PM position is:

  1. Join a multi-manager hedge fund that has clearly defined career paths and promotion criteria.
  2. Move “as close to the alpha as possible” by working in a smaller, siloed team where you can take more credit for the results.
  3. Assume more of a managerial role and develop direct relationships with the LPs so that you can point to results such as AUM growth.

The Top Quant Funds

There are almost too many “top quant funds” to list, but I’ll give it a shot.

Some of the top funds include D.E. Shaw, Renaissance, Two Sigma, Citadel, AQR, Point72 (formerly SAC), Quantitative Management Associates, AlphaSimplex, Capula, PanAgora, Acadian, Man Group, Millennium, and Bridgewater.

Some of the larger ones, such as Bridgewater and Citadel, do a lot more than just “quantitative investing,” so they’re not dedicated quant funds.

Then there are firms that are more on the market-making or prop trading side, but which could also be labeled “quant”: Jane Street, Hudson River Trading (HRT), IMC, Optiver, DRW, and SIG are all examples.

Some of these firms, such as Jane Street and Two Sigma, like to hire undergrads, while others prefer Ph.D.’s and other advanced degree holders.

Quant Salary and Bonus Levels

Base salaries for entry-level Quant Researchers at hedge funds in New York are around $125K to $150K, with bonuses worth 50-100% of that.

So, you could potentially earn between $200K and $300K USD in entry-level roles in this field.

Yes, that beats investment banking salaries and private equity salaries, at least for roles directly out of undergrad.

Some quant funds have paid even more than $300K to new hires, with signing bonuses that take total compensation closer to $400K.

After you’ve been working for several years, total compensation moves toward the $500K+ level.

To go beyond that, you usually need to become a Portfolio Manager or win a more senior position at the firm.

At those levels, compensation could go beyond $1 million per year – depending on your results and the firm’s overall performance.

If you’re a Quant Developer or Quant Trader, entry-level compensation is similar, but the salary vs. bonus split may differ.

If you remain a Quant Developer, your compensation will move toward what Big Tech companies pay their mid-level engineers – but it’s unlikely to go much beyond that.

Yes, good code adds value, but if you don’t own a P&L or attract clients’ assets, your compensation will always have a ceiling.

If you’re a Quant Trader, your compensation could move up closer to what Quant Researchers earn or even go beyond it (completely dependent on your performance and how the team splits its P&L).

Quant Hours, Lifestyle, and Culture

Yes, the entry-level compensation in quant fund roles is amazing… but there are some downsides.

For one, it is a stressful job where the weekly hours can extend up to 60-70+ per week, depending on market conditions.

The average is closer to 50-60 per week, and like sales & trading roles, you’re busy during the entire day with little downtime.

If you’re comparing quant jobs to software engineering at Big Tech companies, the hours are longer, and the stress is greater on the quant side.

Also, tech culture tends to be relaxed and collaborative; everyone is working to build better products, but they’re not directly competing with each other.

By contrast, quant funds tend to be more cutthroat and competitive, and there may be a lot of “siloing,” where teams do not share ideas or insights.

Not every firm is like this, but in general, the atmosphere is quite different from the one in tech.

You are there to make as much money as possible – not to sit around playing games or chatting with your co-workers while doing a few hours of “real work.”

Quant Fund Recruiting: Who Gets In?

The biggest myth about quant fund recruiting is that you “need” a Ph.D. in math, physics, statistics, or computer science to break in.

There are plenty of Ph.D. holders in the field, and some funds do prefer to hire Ph.D.’s, but the degree is not necessary to win offers at all funds.

If you don’t believe me, look at the way Citadel describes its “Quantitative Researcher” position:

“We are seeking top undergraduate, master’s, and Ph.D. students who are entrepreneurial self-starters and enjoy being in a fast-paced and dynamic environment for exciting opportunities in our automated quantitative trading businesses.”

The reason for this is simple: most of the math used at quant funds is not that advanced.

It’s closer to what undergrads in technical fields need to know (multivariable calculus and differential equations) than it is to the level required to understand Andrew Wiles’ proof of Fermat’s Last Theorem (for example).

Oh, and if you’re interviewing for Trader or Developer roles, your coding skills matter more than your knowledge of advanced math.

To have the best chance of breaking in as a Quant Researcher:

  • Be a fresh graduate from a solid-to-top-tier university. Pedigree still matters at quant funds, but less so than in fields like IB/PE.
  • Intern at quant funds, prop trading firms, or tech companies, or complete other math/statistics/coding-related roles.
  • Complete a “mixed” technical degree, such as something that combines elements of math, stats, and computer science. A pure math or physics degree will be much more difficult and won’t necessarily provide a big benefit.
  • Do your own side projects, such as automated trading strategies based on academic papers, and produce results and backtests.
  • Compete in math competitions, such as the Putnam, that require creative solutions to tricky problems based on high school and undergrad-level math.

Hobbies, activities, and leadership experience won’t necessarily help with quant fund recruiting because they only care about your problem-solving skills.

Some of the larger quant funds conduct on-campus recruiting and offer online applications; for the ones that do not, old-fashioned networking via LinkedIn and email is your best bet.

If you have completed a Ph.D. or you’re working toward one, you’ll almost certainly interview for Quant Researcher roles.

In this case, you need a demonstrated interest in the financial markets to succeed.

There are plenty of academics who are “good at math,” but unless they have a serious interest in the markets, trading, and investing, they tend to perform poorly at quant funds.

You can prove your interest with relevant side projects you release on GitHub or closely related internships.

If you interview for Quant Developer roles, you’ll have to complete coding exercises and whiteboard problems, similar to tech interviews.

For Trader roles, take a look at the article on prop trading careers to get an idea of what firms want in candidates.

That same article also has suggestions and resources for practice coding exercises.

The Quant Fund Recruiting Process and Interview Questions

Firms that use on-campus recruiting follow the standard process: they’ll give you an online test, move to HireVue or phone interviews, and then do back-to-back interviews with several full-timers.

If you’re an experienced candidate, it’s common to go around in circles interviewing with funds indefinitely.

Many quant funds don’t necessarily want to hire anyone, but they always want to get new strategies that have worked for others.

So, if you keep going through interviews where they ask increasingly detailed questions about your strategies but don’t give you a decision time frame, you may want to reconsider the fund.

Interview questions at quant funds are beyond this site’s scope, as we focus on accounting, valuation, and corporate finance topics.

But you can expect a wide range of math, probability, and statistics questions, so you should prepare accordingly.

A few recommended resources include:

Quant Fund Exit Opportunities

And now we arrive at the major downside of quant fund jobs: the exit opportunities aren’t so broad.

Your main options are:

  1. Stay in the role and keep performing well, even if your job title stays the same (not an exit opportunity).
  2. Win a promotion to PM or a managerial role where you’re leading a team but not necessarily doing day-to-day technical work (also not a true exit).
  3. Move into other trading/investing-related roles, such as prop trading, or win a quant trading role at a large bank (lower pay, but more job security).
  4. Join a tech or fintech company that’s seeking candidates with programming/statistical skills.
  5. If you have a Ph.D., return to academia.

And… that’s it.

Getting into fields like investment banking, private equity, equity research, corporate development, corporate finance, or venture capital from a quant fund is unlikely, especially if you’ve been in the role for 5+ years.

The skill sets are too different, and the important points in some of these roles – such as deal negotiations – are useless in quant roles.

It’s not impossible; we have covered stories of readers who left quant roles and broke into fields such as equity research before.

But it’s also not likely, and it gets more difficult the longer you stay in a quant role.

Turnover at quant funds also tends to be high, especially among Ph.D. and other advanced degree holders.

These degree holders are extremely smart, but many of them have no interest in the financial markets.

They want to solve math puzzles or work on proofs all day, which is not a recipe for success when you need to generate profits for your firm.

So, Are Quant Funds the Future?

As you can tell by this article’s tone, I am less bullish on quant funds than many other people.

The main problems are:

  1. It’s a mature/crowded industry – This was less true in 2000 or 2010, but as of 2020, it has become more difficult to find winning strategies that continue to perform well over time. Also, “quants” have become a bit commoditized, and many strategies are dependent on buying massive amounts of high-quality data.
  2. Performance has been mixed – Quant funds have performed poorly over the past few years, and so far in 2020, they’ve underperformed the average hedge fund and the average U.S. equity mutual fund. After some strong results in a few years of the past decade, fewer than 20% of quant mutual funds now outperform the broader market.
  3. You don’t develop a broad skill set – If you decide you want to make a total career change, you might need business school to make it happen (unless you’re starting your own company).

Quant Fund Performance
So, I’m not convinced that quant funds are going to take over the world.

If you’re thinking about pursuing quant fund jobs, it’s similar to the sales & trading vs. investment banking decision: S&T can be good, but it is a more specialized opportunity.

Quant funds offer an even more extreme version: they can be very, very lucrative for the right person, but they do not have the broad appeal of IB and related fields.

And since everyone likes pro and con lists, let’s close this article with such a list:

Quant Fund Pros

  • Extremely high starting compensation, with the potential to earn $500K+ within a few years… if you perform well and you’re at the right firm.
  • Recruiting is more accessible than IB/PE recruiting since you don’t necessarily need to start years in advance or attend an Ivy League school – you just need solid math/probability/coding skills, a technical degree, and some work experience.
  • The work can be far more interesting than anything you do at large banks, at least if you enjoy math and coding challenges.
  • The culture and lifestyle can be much better than what you’d get at a bank, as you’ll work less and have more time for outside activities.

Quant Fund Cons

  • Exit opportunities are limited, especially if you want to move out of math/coding/data-oriented roles and do something broader.
  • Promotion can be quite difficult because it’s tough to claim “ownership” of your P&L, and it is increasingly difficult to find strategies that perform well over long time frames.
  • The culture at some firms can be cutthroat and competitive, so you should not expect the warm/fuzzy feelings you’d get at tech companies. Turnover can also be high, and many people don’t last beyond their first few years.
  • The industry is far more crowded and mature, which means that quants have become more commoditized.

It’s not worth it to break into a quant fund and “stay for a few years” before figuring out what you want to do.

So, if you could see yourself working on math/stats/coding problems related to the financial markets for, say, 10+ years, quant funds could make a lot of sense.

Even if you get tired of the work, you’ll have earned so much money over that period that you can go off and do something else – as many professionals do.

You won’t have enough to buy a yacht, but you will have enough to relax and pursue personal interests for a while, do volunteer work, or take a lower-paying-but-more-fulfilling job.

On the other hand, if you want a broader skill set, you’re not sure what you want to do long-term, or you do not want to work on math and coding problems all day, quant funds make less sense.

That’s the best way to decide, even if it’s not exactly a “quantifiable” question.

Further Reading

If you liked this article, you might be interested in reading:

About the Author

Brian DeChesare is the Founder of Mergers & Inquisitions and Breaking Into Wall Street. In his spare time, he enjoys lifting weights, running, traveling, obsessively watching TV shows, and defeating Sauron.

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Read below or Add a comment

  1. Hey Brian, Do you think getting an undergrad degree in data science will be a good option for getting the quant researcher or quant trading role at a big quant fund? By the way thanks for the article.

    1. You can do it with a data science degree, but you’ll probably need to do some extra work to prove you know the finance/stats/programming to make it work… because “data science” is a bit of a vague term that includes programs spanning a huge range of difficulties and topics.

  2. Hi Brian,

    I think there is a preference for PhDs as a PhD is more likely to able to figure things out on their own especially if confronted with something with no known solution.


    1. There may be, but the point here is that you don’t “need” a PhD to win quant fund roles, necessarily. Yes, some firms/groups prefer it, but it’s not a universal requirement.

  3. Hi Brian,
    Many thanks for this amazing article! I have two further questions.
    1) Do you think that getting the CFA certification could make promotion from quant researcher to PM faster/more likely to happen?
    2) Is there any difference in salary between a PM working at a quant vs non-quant hedge fund?

    1. 1) No, unlikely, I don’t think anyone in quant cares about the CFA.

      2) There are some years in which quant funds outperform or underperform, which can explain the salary/bonus differences. But if you adjust for performance differences, no, not really. The main difference is that quant funds tend to be more expensive to start and operate, so salary/bonus levels at lower AUM may be limited.

      1. Many thanks for the answer.
        If the CFA is not useful in the transition from quant researcher to quant PM, what else could be useful? I have been reading some complaints from quants who would like to be promoted to PM but don’t succeed because they don’t have a personal track record, which they say is a bit of a paradox since the only way to have a personal track record is to already be a PM… Can you clarify on these situations, especially at large/top quant funds?

        1. I don’t know enough about quant funds to say, sorry. You have to get into a position where you’re making more of the decisions or get more unofficial responsibility, despite not being a PM yet, so the answer might be to go to a smaller/growing fund where you can do that more easily (after working at a larger one first for experience). But this is just a guess, and I honestly don’t know enough about this field to give specific tips on moving to a PM role specifically at a quant fund if you have trouble proving your track record.

        2. Great article Brian!

  4. Hi Brian, thank you for your great article ! Since you seems knowledgeable on this aspect, I had some questions for you if had time.
    I am an engineering student studying maths. I have to choose very soon my path between 2 great french universities, one for quants (El Karoui) and the other for IB (HEC), but I have no idea what to do.
    I like maths but I am afraid that quant hasn’t a lot of opportunities, as you wrote in your article. However, I am afraid that my education in sciences would be a lost opportunity if I go in IB. What do you think ?

    1. The only way to decide here is to complete an internship in both fields and see which one you prefer. In general, it’s easier to get into quant funds a few years out of school if you did something else beforehand, while it’s very difficult to do the same for IB. So maybe start with IB, and if you don’t like it, consider applying to quant funds.

  5. Hi Brian,
    Thanks for this article. I’m an incoming college student at JHU majoring in math and CS (minoring in accounting) who had a few follow up questions if you had the time:

    1. For someone who eventually hopes to expand a ~US$100M family business(mainly assets right now with low cash flow)/start my own, would you recommend starting off in IB/PE or quant or tech? My parents want me to go for tech since it’s the “future” lol, but I’d presume the skill sets/connections gained if I manage to break into IB/PE would be more useful. Quant trading is also attractive to me, but mainly because of the more lucrative pay. If going into tech, I think I’d try for product management roles rather than SWE, which I think suits me better. I’d love to hear your advice.

    2. For IB, is it okay if I’m a CS/Math double major with an accounting minor? I want to keep my options open for tech too, which is why I have CS as a major. JHU doesn’t really have a finance/accounting major, and from what I’ve noticed the people who get into IB from here are mainly Econ majors. Do you think I need an Econ major or is my current combination okay?

    3. Is it possible to break into IB after a freshmen tech internship at FAANG? I know this is really presumptuous but if I were to land a FAANG internship for one of their freshman programs, how would that be treated? Could I leverage that to get into BB/EB TMT/Technology IBD in SF come Junior year, considering I land an IB internship sophomore year? For better or for worse, I also count as “diversity” so I’m thinking of applying for some of the sophomore diversity programs at the BBs. Currently, I’m attempting to land an internship at a small PE/VC firms (if this doesn’t workout, I’ll reach out to a high school alum who manages a small tech consultancy)

    3. Lastly, how is JHU treated in IB/PE? I know even though it has prestige, it’s not a target as it’s mainly known for medicine, but I guess I’m just looking for some reassurance that I don’t need to try and transfer to a more traditional target.

    1. 1) Your first question is too open-ended for me to say anything specific. What is your exact plan? Work for 2 years and then go to your parents’ business? Work for 5-10 or 20 years and do that? What are you actually interested in doing? Is your personality better suited for sales/client roles or programming roles?

      2) Yes. Econ is a generally useless major anyway.

      3) Probably not unless it’s a corporate finance internship at one of those companies. Otherwise, you need something closer to finance. Yes, the name helps, but they’ll still view it as an engineer making a career change.

      4) It seems to be a semi-target. If you can get solid internship and start early, I don’t think you need to transfer unless you are 100% set on Goldman Sachs and cannot accept any other possible outcome in tech/finance.

  6. Marcos Jaen Cortes

    First of all, great article! It was a pleasurable read!

    My professional goal is to end up in the board of directors of a bank in my home country. I realized that most people in these roles come from old money, and the ones who don’t, studied and work abroad for a while, and then landed a good position in a bank. Most of their backgrounds where non quantitative, they bachelors in law, or MBAs, or traditional finance/econ degrees.

    I am a third-year international student at a top university in Canada pursuing a quantitative degree. My enquiries are the following:

    I still I’m open to the idea of pursuing a MFE straight out of ug as I will need it to be competitive and to be other to move/stay in a first world country where most quant jobs are and where pay is significantly better. I have read that in Europe, quant jobs are less demanding than in North America, obviously pay is lower, but when you take COL and QOF it evens out. Do you recommend me to do my MFE in Europe, work for 5-7 years overthere to gain some experience to them come back to my homecountry? Or should I just try to break in into a IB or a traditional fiance job after ug. And then pursue an MBA? My bet for route 1 is that banks are becoming more and more quantitative, so when I go back to my homecountry in around 7 years time my skills will be demanded, and as I have experience I will be put in a supervisor role, where I could climb the ladder. What is your perspective in all of this?

    Thanks in advance for any feedback/input! It is really appreciated.

    1. I don’t think any quant role is a pathway to joining the Board of Directors of a bank. Joining the Board is completely dependent on relationships and networking, and you don’t really do these in quant roles. If that’s your goal, you are better off going for non-quant roles such as IB, PE, corporate finance, etc., and advancing up the ladder until you have good relationships in the industry.

  7. Alexander

    Great article. What about moving from a quant fund into data science & analytics roles, that are sprouting up in M&A houses, that are meant to bring another sort of analysis to the deal process and to the client. Think PWC deal analytics. EY Valuation Modelling Econs. Even Moelis has a unit dedicated to this. Can quants move into such units and acquire a broader skill set to move into more corporate finance work

    1. It’s possible. Unfortunately, I just don’t know much about it and have little information since it’s such a new area. But I think you have to be careful because some of these roles do not really seem “front office” despite the names.

  8. Hi Brian,
    I interned in quant research at a large (but not considered prestigious/coveted) AM last summer (after my junior year). I’m now planning to get my master’s but don’t know what to do with this summer after my senior year. None of the BB’s I’ve talked to were interested in a graduating senior, and I’m not sure where to turn to. Any suggestions of what to do?

    1. Maybe work on a side project that you post on Github or contact small/startup investment firms in your area and ask about internships? A lot of the smaller funds will not necessarily care that you’re graduating if they still need interns for certain work.

  9. Hi Brian, thanks for the great article! I am a recent finance graduate in Canada with internships at a small IB boutique and operations startup. I am pursuing lv 2 of the CFA, learning Python/VBA and considering enrolling in a remote part time degree (scholarship money left over). Would you suggest pursuing a master in finance or diploma/master in analytics/coding?

    I would like to continue trying to break in to IB or ER but also interested in pursuing product management in tech/more quant heavy role in finance.
    What are some of the best paths going forward regarding degree and work experience?

    1. Thanks. A Master’s in Finance would be more useful for the IB/ER route, while the analytics/coding degree would be better for tech or quant roles in finance. So it really depends on which one you’re more interested in.

      It is quite difficult to win IB/ER roles in Canada because the industry is so small (and the top ~5 schools have a lot of students competing for roles), but it is do-able if you put in enough time and networking and have the right credentials. I’m not sure how big the quant industry is there, but it’s probably about as difficult as breaking into IB/ER.

      Tech roles are easier to win, but the pay ceiling is also lower unless you’re at one of the FAANG companies.

      But I think you need to decide if you want to go “all in” on IB/ER or aim for tech or quant roles first because it will be difficult to pursue all of them at the same time. If you don’t already have coding experience or a technical degree, I think it may be slightly easier to pursue IB/ER roles because you already have the IB internship and the CFA study.

  10. Amazing article – just what I needed. Thanks.

    1. Thanks for reading!

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