Quantitative positions within finance can be broadly categorised into four main types. They are the quantitative trader, quantitative researcher, financial engineer and the quantitative developer. They are all essential positions within the financial community, but have very different characteristics regarding perceived importance, levels of pay and career progression.
The quantitative trader is typically "top of the food chain" in the quantitative financial community. This is because they are generating trading revenue for their employing firm - either a bank (on a prop trading desk) or a quantitative/systematic hedge fund.
The quant trader will spend their time designing algorithms that search for alpha, the elusive returns above those returned as a component of standard stock market fluctuations. These algorithms often have a heavy econometric, statistical or machine-learning character, and so quant traders often have PhDs in Artificial Intelligence or Applied Mathematics.
A career as a quant trader can be extremely lucrative if the firm (and trading group!) has a runt of good trading years. It is not uncommon for the best quant traders to be retiring in their mid-to-late twenties!
The quantitative researcher is usually a pure mathematician or PhD in stochastic calculus, who has decided to take on a more applied role than academia. They can often be found in alternative research firms or some of the larger hedge funds, working on more "blue sky" approaches to gleaning market returns. However, quant researchers are also employed by investment banks - but usually in a 'Middle Office' capacity, as these researchers will not be spending much of their time implementing models - they will usually pass their work onto a financial engineer or quantitative developer.
The financial engineers are generally the people who are referred to when the term "quantitative analyst" is utilised. They are tasked with taking a product, often sold by sales teams to clients within large banks, and figuring out how to correctly price it. This will involve the tools of stochastic calculus and risk-neutral pricing, as well as the ability to implement the model into an already existing library, built with a language such as C++, C# or Java.
The financial engineers are often found in the fixed income and foreign exchange asset classes, where derivative products are prevalent. A financial engineer will often have a background in physics or engineering - utilising their modelling skills to implement new financial products.
There are generally two types of quantitative developers or quant devs in the financial industry. The first type will work closely with other quantitative analysts to implement and optimise their financial models. In practice, this means taking a prototype code from MATLAB, R or Python and rewriting it in another language such as C++ or Java. These quants will often be close to the money and will reside in the Front Office of an investment bank.
The second type of quantitative developer will deal with financial pricing data and trading systems architecture. They will be coding up the raw infrastructure allowing the quant analysts/traders to run their models on and make money. In practice, these means hooking up databases to "business logic" and brokerage APIs. In investment banks this can mean working on maintenance of large-scale legacy systems or, if employed in a fund, working on "greenfield" projects related to a new trading algorithm. In banks, this will typically be a Middle Office role.
The one extremely high-paying role that sits in the quantitative development arena, is that of the star C/C++ developer who understands Unix network programming, low-latency systems and the ins and outs of the Linux Kernal. These individuals can often be found working in the secretive world of Ultra High-Frequency Trading (UHFT), where trade orders are now measured in microseconds. If an individual possesses this particular skill set, they can command base compensation packages of $250k and above!