A Quantitative Analyst – colloquially referred to as a ‘quant’ – uses mathematics and statistical methods often in one specialised area of finance and investment management. Given the technical nature of the work and the domains of specialisation (i.e. a Quantitative Analyst could work in a wide range of areas from derivatives to algorithmic trading), the path to becoming a quant can often be ambiguous.
In order to become a quant, it is essential to have understanding of the types of tasks that are done on a day-to-day basis and the skills required to excel at those tasks. As mentioned above, there is also huge variation on the types of tasks depending on your specialisation. The common threads amongst those specialisation will be programming, data management/analysis/scraping, and number crunching. Therefore, the skillset required will be exceptional quantitative skills, knowledge of relevant programming language and deep knowledge of how these apply in a financial context.
Unfortunately, the path to acquiring these skills is not
as simple. There are a myriad ways to acquire these skills. The most obvious starting point is ensuring deep mathematical understanding, coupled with knowledge of finance. This can be gained through most high-level quant degrees and can …