Quants and Data Scientists

[Franko]

Hello!
I have often heard that a lot of modern quant positions require good knowledge of Data Science and it's instruments very well (R, Python and so on). And many quants change their career to the Data scientist's career and vice versa without problems (These jobs have a lot in common).

Is that really true today? What do you think about it?

Regards,
Franko

 

[yetanotherquant]

Hi Franko,

being both quant and data scientist I would not say that the transition "quant <--> data scientist" is straightforward. And in practice these domains have not so much shared stuff (well, unless you develop statArb/quantitative trading strategies).

As a "classical risk neutral quant" your tools are change of measure/risk neutral pricing, trees/finite differences/PDEs, [Least-Square] Monte-Carlo.
Your main programming language is C++.

As a data scientist you, first of all, must be able to preprocess your data.
Then of course you must be fit with databases, R (both statistical models and data visualization) and - if you are working with big data - with Hadoop Suite.

But of course both professions require solid numerical fundamentals, in this sense a quant can become a data scientist and vice versa (IMO vice versa is harder because the risk-neutral pricing is a deep non-intuitive idea).

 

[Franko]

Hi Franko,

being both quant and data scientist I would not say that the transition "quant <--> data scientist" is straightforward. And in practice these domains have not so much shared stuff (well, unless you develop statArb/quantitative trading strategies).

As a "classical risk neutral quant" your tools are change of measure/risk neutral pricing, trees/finite differences/PDEs, [Least-Square] Monte-Carlo.
Your main programming language is C++.

As a data scientist you, first of all, must be able to preprocess your data.
Then of course you must be fit with databases, R (both statistical models and data visualization) and - if you are working with big data - with Hadoop Suite.

But of course both professions require solid numerical fundamentals, in this sense a quant can become a data scientist and vice versa (IMO vice versa is harder because the risk-neutral pricing is a deep non-intuitive idea).

I also think that Quantitative Analysts are much closer to Data Scientists than "classic" Quantitative Developers because their positions often require knowledge of R, SQL, Big Data and so on...