Any Financial Modelling Podcast listener will know that data is a passion of mine. In the past few years, the finance world has woken up to the power of data – from hedge funds to traders. Citadel, the American hedge fund and financial services company, recently indicated its desire to have top data talent, but poaching from a rival firm.
Indeed, it is a rare breed of data analytics expert that understands both finance and the applicability of data analytics in the finance domain, whether that is investment banking or fund management. I have spoken before how the effective data scientist requires domain expertise, however many data scientists are not interested in structured finance, and vice versa (and I’m talking about corporate finance and investment banking, not quants who have been in trading and global markets, or retail banking, for at least a few decades).
Make no mistake though, these data scientists will face the same challenges as data scientists in every other industry, from having to be a data ‘janitor’ to wrangling large amounts of structured and unstructured data from various places.
Ultimately, as data scientists become prevalent in every industry, those companies without data scientists will come under more pressure to perform and look for the edge. Data scientists will continue to add more value as they become domain experts – and this will lead to the next revolution in data analytics as it starts to deliver exponential value to business.