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 Mid Career Switch - Data Science?, from Process Engineer background

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chromatino_hex
post Jan 18 2022, 06:13 PM

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Joined: Aug 2020
QUOTE(buffalowings @ Nov 13 2020, 10:42 PM)
data analyst, business analyst, business intelligence analyst, finacial analyst bank analyst, database programer, statistician, market researcher , sales analyst and many more thinking they are data scientist and assuming data science is just about understanding data or extracting data or doing SQL or putting data in nice graph for management to understand using Power Point ......thats why the market is flooded....a data analyst is imho is way far from being a data scientist...its like someone who just started learning how to speak claiming can publish a song album ....hahaha.....not to butt hurt anyone .....but if you dont know how to put together a solution that makes use of technology to process data via statistical modelling or ML ...you are just...a normal analyst..and not a data scientist.....unfortunately even organizations have diff thoughts wat a data scientist role is so good luck....know a telco GM who never done tech and from a sales background....was head of data science because he claims he understands data.....hence anything else can outsource to engineers...the most important thing is that he can interpret data better than less experience person.....(wat a joke)

a data scientist should know how to implement a real world data product and not just to story tell about data (this is like basic)... for a simple example......how to build a recommendation engine, how to create a credit scoring system or how to build a system to detect data phising ........and not just to report sales trend or answer what was my top selling product, which customers bought it  and give a recommendation how to improve those reporting insights? (this to me is just analyst role using descriptive analytics basic skill to have)........as a  data scientist you would know how to build a working prescriptive analytics solution end to end with constant data input and output.and it you are real good a solution that can slef learn......and nearlly 99 percent of the time...its a solution where a human cant interpret the amount of data that need to be analyzed....hence why is called big data.....for example netflix engine goes thorugh a billion customers viewing behaviors via clicks and interaction with thier product......and then use a statitcal model to find similliar patters for up to >50 movies recommendation for 1 person...similiar with facebook updates you see...they are personalized to a single individual based on algorithms that read billions of interaction the user of the world have with facebook.....a human analyst would not be able to interpret it........hence why you need data science........and data scientist that build data science products.......not a just hjire some one who can find data and interpret via excel.....or BI......that IMHO is an analyst......and you dont need a Masters for it....just go have on th job experience but please dont think u are really doing data science.......you just lying to yourself by having an inflated title....

another good example is alpha go which uses neural nets to study millions of players moves and then come out with a solution to beat a human player as well as IBM Deep Blue for Chess...the solution has to real time and via each move the human makes it predicts what the best move to make and do it real time.....based on its experiences from millions of possible combination.......a human wont be able to process such vast amount of data....if its possible then we only need an Analyst to give insights to the CHess / Go player in Powerpoint for wat should be the next move......lol

Hope the above shares why data science can be such an exciting and well paid job if ppl understand what it should and can do.......

and why if use just for analysis, insights and post event action recommendation by humans there is 1000 capable ppl can do this unlike the above where is a combination of technology and statistics and subject matter data (millions).....to provide realtime actions.....but like i mentioned earlier the other devil is more and more techs developers (google / Miscrosoft, AWS) are findings ways to automate the data science work using various Auto ML tools......so hence might be too late to the game .....where in the future you can buy data science off the shelf.......so probably a dat science wont get a high premium but definitely could be better than pay than an analyst....but likely be lower that a legal professional such as Accountant, Lawyer or IR Engineer where expertise in an subject is not easily duplicable by machines or  humans.....

if everfyone can do it.....u wont be as valued.....if only limited ppl can do it....then u r an expert in that area and can ask for a premium in salary......a Masters. /  PHD is window dressing that can open nice doors but cant help you to create the work........or maintain the role if you dont really know the job....
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someone who doesn't understand about statistics/DS talking about statistics/DS lol

Brother, go back to school and get an A+ in probability and statistics and then revise your statement. Recruiters are not dumb; they can smell a fake Data Scientist from a mile away when asked to explain about concepts like Markov Chain or a Tukey test

This is exactly why companies should hire Mathematics/Statistics/Actuarial Science/Computer Science graduates only. Set a barrier of entry for Data Science.

This post has been edited by chromatino_hex: Jan 18 2022, 06:15 PM

 

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