hi jgyy,I wonder how much different of a data analytic role be in these 2 companies. And I also wonder how come the requirements for data analytics are lower than the other 4 tracks.
how much different of a data analytic role in SGX and Dymon?
this is an interesting question.
SGX is in the business of market operator and surveillance. Millions of of transaction take place at the exchange daily, be it equity trading, futures, options and other exotic derivatives. It also function like a 'policeman' of the marketplace, making every market participant abide by the market rules and 'catch' those that violate the market rules and regulation. As you can see, it has alot alot of data on a daily basis. with so much data, SGX is a perfect place for data scientist to pull the data, clean them, put them through some statistical learning models, make some business sense out of them, and present the insight to the management and stakeholders in the form of data visualization. Another huge use of market data is to use to catch crooks who try to manipulate the market to their advantage, in the hope of making money in an illegal way.
As for Dymon, a hedge fund, it's sole existence is to make investment gain in the market for it's investors. it has no public duty to perform like SGX. hedge fund is out to make money through their trading or investment strategies. usually, they have finance quantitative guys who are well versed in programming and statistics, who research the market to derive alpha value (fund return - market return) the trading models that they created. hence, you will expect the data analytics aka scientist folk there to do very different things from the folks at SGX. very stressful job but paid alot to be stressed. lol.
given that the data analytics track is 18 months instead of 24 months, i would think that the TFIP DA track focus primarily on training how to clean the data, do exploratory data analysis and especially data visualization since they are the folks who will present their data insight to the management or stakeholders. if the DA training also goes heavily on statistical learning and modelling, then the trainees will receive a full spectrum of a data scientist training which will likely take more than 18 months.
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