IMHO a lot of people are switching into data science hence will have lots competition when you graduate....and pay wont be good as now.....i seen over thousands applicants for a data science job........and from every background....

There are some people with 20 years of experience from banks / insurance using SAS at that time was called only Predictive Analytics....and then there are tons of fresh graduates (ADAX and etc) in data science (R / Python) plus people wanting to switch because data science seems cool (due to hype) switching from customer service, insurance , bio / engineering even IT and accounting grads with all studying masters . phd or coursera yet dont know how complex it is to do data science.....u need to know the whole eco system from data (as in unstrutured n strutured n relational n non relational n etc, statistics, programming and most important subject matter (marketing, risk, manufacturin, ai, visual, hr or....)

the work of a data science varies from industry to industry.....in a factory it might be used for predicting machine failure or faulty products.....and in real estate to predict property price.....the alogrithims and how you get the data will vary as well......some u need yo get data from unstructured sources and some from databases/store and databases/store have many types - rdbms, nosql, hadoop and then how to transform the data to your prediction model (poisson? / binomial / exponential, normal).... u will need to know stuff like json, hdfs, sql, phtyon, r and how to join those datasets .and bloody more....the risk of automation of your job with the rise of Auto ML..

Data Science is a tough life.....and with many competition now. (like aspiring actor / singer)....pay has dropped drastically.... most asiprants calls them self and think they can do data science without even knowing at what level they are performing.......with most boss and organizations have different idea of what a data scientist is and can do........the worst expectation is 1 data scientist can build all AI stuff without a team.....met an low cost airliine Chief Data and he aspirationw as to build an algorithm to define the whole airline and he was a reputable startup bur never had any programming or data backhkground..and a CTO of a Telco M that wants to use data science to build AI to replace CEO and management as he feels data / AI is better than humans.........lots of hot air......data science is nots just math, not just porgramming and not just reporting......and definitely not just an AI that can talks to you like human do

We have engineering PHDs, Business PHDs, even Real estate PHDs doing data science yet never know how to code before............just talk.....and with automated machine learnings/data sciences tool not sure we need so much data scientist in the future....even if need probably be like current engineers / SAP consultant salary not gonna be high pay unless you can be a real unicorn ie full stack data science.....knows everything in data tech, programming stats and business and make sure you keep up when it evoles......

so yeah currently every tom dick harry ahmad mutu sammy wants to be a data scientist...becasue the have some wrong impression of the work and future pay....

better do a doctor...or lawyer or accountant if you are starting out only now.....pays higher and more secured work......and probably next few years data science is just a tool like excel.......any normal person can just use without programming or understanding the inner works.....

similarly in the 80's everyone wanted to be an Engineer / Pilot.......now engineering / pilot role is not as lucrative as Marketing and Sales......

i feel data science and digital will have web designers / DB Administrator fate in the future........unless u really stand out......new and cheaper person or automation(web templates, word press, what you see if what you get tool for exmpl) can replace u

oh yeah thing is that is funny to me ....most data scienctist can come out with a model ie regression, classification , nueral net to predict test cases.....but how to prodcutionalizxe it in real world clueless......for example.....how embed those predcitions into your system...ie example (grab app for predicting traffic, netflix form recommendation of films, predicting fraud when someone tries to do a transaction on online banking)...you cant simply run/embeb R or SAS or Python in IOS app or C++ solution.......which will pull real time data from your data sources...food for thought..

This post has been edited by buffalowings: Nov 13 2020, 10:31 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....

This post has been edited by buffalowings: Nov 13 2020, 11:36 PM

exactly......