Quantitative Finance Careers Guide

*Being a quant combines the best aspects of intellectual stimulation, state-of-the-art research, development of mission-critical tools and lucrative compensation.*

Quant finance is at the forefront of mathematical, computational and statistical research, driven by the relentless pace of financial innovation. The role of a quant—be it trader, researcher, analyst or developer—is thus extremely rewarding from an intellectual point of view.

Throughout the last thirty years quants have been using the most cutting-edge technology to solve extremely challenging problems in risk, asset pricing and software development. It attracts talent from the best global schools leading to a peer-based learning environment similar to top-tier universities. Many quants are lucky enough to experience a thought-provoking and collegiate, albeit fast-paced, workplace.

Quants are also very well compensated. Funds, banks, family offices and prop trading houses realise what quants bring to the table. They are often situated in the "front office" close to the trading desks. In quant hedge funds the quants *are* the traders and thus well remunerated on a "profit and loss" (PnL) basis.

The role of quantitative analysis within finance has a long heritage. This relationship between the two is likely to continue for some time, not least due to the staggering growth of data abundance. In our view betting on a quant career definitely has a strong risk-adjusted return!

Find out more about the latest quant trends here:

"The role of a quant—be it researcher, analyst or developer—is extremely rewarding from an intellectual point of view."

*The quant finance landscape has shifted significantly in the last five years. The decline of derivatives pricing and growth of alternative data has generated a strong demand for quant developers, traders, risk managers and data scientists.*

The majority of quantitative roles within finance all require a background in mathematics, statistics or computer programming. Beyond that the roles differ substantially.

**Quant Trading Researcher** - Quant traders spend their time researching and designing algorithms to produce "alpha" - new uncorrelated returns streams. They generate trading revenue from the firm and hence are well-compensated, often on an equity basis. Quant traders are highly-skilled researchers in mathematics, statistics, machine learning or other areas of scientific modelling.

**Quant Developer** - Quant software development is extremely broad in quant finance. On one end of the spectrum are engineers who spend their time building infrastructure for data storage, pricing and trading. On the other are extremely well-compensated developers/traders who work in High Frequency Trading (HFT), possessing exceptional skills in C/C++ as well as low-level kernal development.

**Quant Analyst** - Quant analysts—or financial engineers—are tasked with the pricing of exotic derivatives products. This involves stochastic calculus and risk-neutral pricing methodology, often using deep areas of mathematics. However these quants are also required to be well-versed in C++, C# or Java, in order to implement these pricing engines. However, the market for quant analysts has reduced significantly since the 2008/2009 crash.

**Data Scientist** - Data scientists blend statistical insight, machine learning savvy and software development expertise in an attempt to extract useful signals, often from extremely large datasets. With alternative data now becoming important to the bottom-line of major financial firms, data science skills are in high demand within the financial sector.

**Risk Manager** - The increased compliance and regulatory overhead for banks and funds has generated significant growth in the area of overall firm risk management. Risk managers are often highly-trained statisticians, with a financial background, and carry out an important role in the workings of investment institutions.

To find out more about the roles on offer in quantitative finance take a look at the following article:

"Quants are often highly-skilled in mathematics, statistics, machine learning or other areas of scientific modelling."

*Quant traders often come from a research background in mathematics, statistics or machine learning. Quant developers often come from a computer science or software development background.*

There is no avoiding the fact that quant careers involve a lot of mathematics and coding. Hence it is necessary to convince employers—or recruiters—that you possess the necessary capabilities.

Usually the most straightforward path to obtaining these skills is via formal study to undergraduate, Masters or PhD level, depending upon the desired role.

However, many successfully make the transition from other fields after a long career—particularly in technology startups, engineering or academia.

The following articles outline in detail the educational steps necessary to obtain a quant finance interview at a reputable firm:

- Best Undergraduate Degree Course For Becoming A Quant?
- How To Get A Quant Job Once You Have A PhD
- Can You Still Become a Quant in Your Thirties?
- Which Programming Language Should You Learn To Get A Quant Developer Job?

There are many more articles on QuantStart about how to become a quant. Please take a look at the list of articles here:

If you have any questions about becoming a quant, or quant careers in general, then please send an email to support@quantstart.com and the team will be in touch.

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