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Data Science Landscape in SG

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Old 15-10-2019, 10:47 PM
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Default Data Science Landscape in SG

Hi there

Could not find any threads on this forum on this topic. Would like to know/find out about the DS landscape here, which companies have established teams working on DS and the average salary.

Anybody here working in this industry would love to hear from you!

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Old 05-12-2019, 06:52 PM
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Quote:
Originally Posted by silverlineage View Post
Hi there

Could not find any threads on this forum on this topic. Would like to know/find out about the DS landscape here, which companies have established teams working on DS and the average salary.

Anybody here working in this industry would love to hear from you!
Data Science is wide....which area you referring to?

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Old 12-12-2019, 07:18 PM
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DS is a bubble waiting to implode. Unless you're ML or hold a Phd, everything else can be done with software.



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Old 13-12-2019, 04:21 PM
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Hi, I have been working as a Data scientist for a while now, way before the current craze, and I thought I can provide some perspective on my personal observationd.

DS is a super ill-defined term. Job scope, pay, and responsitilies differ widely between company/department/team. As a rule of thumb, your pay increases when you have more experience and/or more reponsibilities. Industry matters too - In general, banks pay more than manufacturing for the same job level. There are salary reports which you can easily google to get a sense.

DS jobs are also not created equal. You can be designing new algorithm, implementing new algos created by others, building models using packages, bringing models into production, cleaning data, or building an excel dashboard. Pay will depend on the supply and demand - if you can find an opportunity that that the employer "thinks" you are the only who who can do the job, you will get paid handsomely. So always make sure you are in demand.

I would recommend that if you are fresh out of school or new to the field, join an established team with some processes put in place. More importantly, choose a manager who knows his stuff. Try to specialise in a field you are interested in. The deeper your specialisation, the less likely you will be replaced with better software.
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