>last 3 jobs as both a data science manager and data scientist
>tried to use machine learning but in each job it is the same story
>The company states in the job description they want somebody with ML knowledge and they know-how to apply ML to solve current problems.
>find out you were hired to do just data analysis in excel or R or Python because no ML currently exists
>find out data is sparse and that the company actually doesn’t have the right features to do what it wants
>real-world problems show a high degree of non-linearity
>the easy canned ML solutions that you learned in college don’t really apply
>typical real-world scenario
>run a model and the model comes back with a 45% accuracy
>not much better than a 25% random guess
>At this point, flipping a coin would be better than machine learning
>find out you are a SQL junkie and you write SQL all day long to retrieve data
>90% of the hype is around getting the data right and building dashboards
>find out you have a manager who is apprehensive about ML because he feels it is a black box
>he is not about to let ML take over even as an experiment
>he feels ML is unpredictable and that the business may lose money
>dreams of putting ML models into production are a pipe dream far in the distant future
>find out IT is not cooperative
>they see you as the hotshot new kid in town with skills that nobody understands
>They are afraid that if they let you take over it will diminish their power
>ML has largely moved to the cloud now
>in order to access those cloud resources and serverless architecture to implement ML in production need full rights
>IT will simply deny those rights because of the aforementioned reasons
>The manager doesn’t want to upset the current working conditions
>bottom line is to keep the current business running
>the priority is not to have you try fancy ML techniques that are unproven which may or may not bring a profit
Born too early
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>lured into the job with aspirations of putting big ML models into production and doing cutting edge algorithm research
>only to find out that the company is not ML ready
>they only hired you so they can say to their clients
> “Yes, we have a machine learning guru onboard”
Sounds great to me. You get to sit around at work doing something noone else understands and which noone actually wants to see in production.
But because the CEO read about the stuff you do in a trade mag a couple years back he's absolutely convinced that unless you're part of the team then the company will be doomed the moment your skills are actually required.
So you can just sit around in your office reading various tech publications for 8 hours a day without doing any actual work but still get paid and without the fear of getting kicked out.
So STFU and just enjoy.
You guys are like a more subtle way of saying "we hired a tranny nigger and here's why you should do business with us!"
Other than a blow to your pride I'd say its a pretty good situation, just work on what you like on company time.
Let's get right to it.
youtube.com
How do you even get a job in data science? I just finished my masters and I have ML projects that I think demonstrate competency and understanding, but I can't get a response on any applications.
Companies don't want theoreticians.
>Join a startup that does shitloads of ml on big data as a platform engineer
>on call sometimes and the only part of our huge pipeline of services that constantly breaks and pages me is the ml shit
>have to fix a bunch of python spaghetti code written by a bunch of math nerds who dont know how to really program
Hate you dumb niggers so much, you waste my time
in my case:
>Got model with 70% accuracy
>Boss tells it should be 100%
>Say that's impossible
>Boss asks for 95%
>Best I can do is 80%, if we lucky
>Boss wants 90%
>Insist 70% is still a viable product and works in the industry
>Model still at 70% after doubling epochs
>Optimize parameters by hand, finally passes 80%
>Boss now wants 90%-95%
>"Should be easy to get another 10%"
>Have to explain how this works in an exponential increasingly dificulty
>Boss says that he cannot sell something with that "low" accuracy
>Dataset is shit anyway, so the %s are phoney anyway and no idea how it would generalize
good luck selling that shit
why hire someone for that when you can shot buzzwords:
>Yeah, we store a deep neural model with markov chains on a cloudlet that processes the microservices and appends the result on a blockchain with k8s so we can add NFTs to the metaverse
and some 6G+ and IIoT and I'm in
This user shows initiative and out of the box thinking and brings working solutions to company problems in real time.
Recommendation: promote ahead of peers.
you faggot got the job
my job interview was just the recruiter complaining that they don't know how data science and statistics could be applied in their business and were not interested in hiring
why the job ad then? wtf
>stealth TOOO OLLLD thread
stop making these shitty demoralization threads you faggot
moron, force me to stop
sorry, you're not a good fit, we want someone with senior level of experience we can exploit at the wage of a junior
After Intro, OOP, and architecture, I can basically get a degree in Python by doing the Data Science concentration. Worth it? Hell even Data Structures and Algos can be done in snake lang.
Bump
>cloudlet
kek cloudlets btfo
fog computing master race
lied about job description, a classic, just happened to me and quit the job after 3 days.