Join devRant
Do all the things like
++ or -- rants, post your own rants, comment on others' rants and build your customized dev avatar
Sign Up
Pipeless API
From the creators of devRant, Pipeless lets you power real-time personalized recommendations and activity feeds using a simple API
Learn More
-
DM'ed a girl on reddit who posted a humorous comment on a post that interests me.
Got to know she's in the same profession as mine.
Few messages later...
Me: How much do you like working as a data scientist in your company ?
(asked her because it is kind of my dream company)
She: You can't really put a number to it. It has many aspects.
Me: How about a vector ?
Waiting for a reply since 3 days.
Do you guys get the joke or was it just me? She claimed to be a data scientist, it's not my fault 😣20 -
!rant
Yesterday i updated my LinkedIn title to Data scientist.
Today morning i got 3 phone calls for job offers.8 -
Data scientist: we need to whitelist a pod to connect to a database
Me: Whitelist? We don't use whitelists on private databases
DS: It's the new data warehouse database
Me: is it on <X> VPC?
DS: I'm not sure what that means but its ip is <real world ipv4>
Me: Are you hosting a publicly accessible database with all our end users information?!
DS: ...
Me: There goes our SOC2 audit controls...
DS: how long until you can white list it?
Me: I won't be whitelisting it. You need to put it on a private VPC and peer with the cluster, you'll have to rebuild all the Terraform and redeploy
DS: We didn't use Terraform because it takes too long, just white list the pods IP.
Me: No. I'm contacting the CISO and CTO...21 -
I was added on LinkedIn by a person who is:
Strategic Thinker & Solution Architect & Innovation Thinker & Data Scientist & CORE Banking & Digital Transformation & AGM & CIO
HOW FUCKING LUCKY I AM TO BE ADDED BY THIS TYPE OF PEOPLE -.-7 -
Just when I thought I'd seen the craziest job ad...
Title: Sr. Lead Data Scientist / Python Developer
Required education: bachelor's in CompSci, Math, etc. PhD preferred (lol)
Required experience: 10+ years in Python development
Other requirements: must be under 25 years of age to qualify for funding from EcoCanada (lmao!!!! y'all trippin)
Who is writing these job ads? I swear they get more insane every day.13 -
I want to thank every Indian computer scientist on Youtube. Because of these guys I passed my Algorithms and Data Structures Exam.10
-
Most of the tech YouTubers are really noob engineers.
Joma was a data scientist. He is an L3 engineer at Google and he hasn't done much during the last 1 year based on his internal stats.
I saw tech leads stats while he was at Google and that dude did nothing during his time. I'm sure he was an IC before he became a lead.
Clement talks about system design bull shit but he's a math major who worked on some angular front end while he was at Google. Basically his experience in tech is mostly involving using mat-button and mat-input. He also quit FB in a month.
Listening to tech lead gives me cancer. That guy was also some front end/ mobile engineer. I don't think any less of mobile engineers but tech leads acts as if he built some large scale systems at Google and FB. His opinion about react native shows how much of a noob he is. He also talked about docker in one of his video which showed he had some fundamental misunderstanding of what docker is. In his courses, he struggles to explain simple algorithms.
I don't know how these people have the courage to claim themselves as some sort of experts in the field when they are extreme noobs. They also sell some shady courses and are robbing innocent college kids.
One thing they all do well is talk. Which I give them 10/10.12 -
I always have guilt complexion of saying that I'm a Data Scientist - when I'm actually spending weeks scraping and annotating data into a csv file.3
-
Most kids just want to code. So they see "Computer Science" and think "How to be a hacker in 6 weeks". Then they face some super simple algebra and freak out, eventually flunking out with the excuse that "uni only presents overtly theoretical shit nobody ever uses in real life".
They could hardly be more wrong, of course. Ignore calculus and complexity theory and you will max out on efficiency soon enough. Skip operating systems, compilers and language theory and you can only ever aspire to be a script kiddie.
You can't become a "data scientist" without statistics. And you can never grow to be even a mediocre one without solid basic research and physics training.
Hack, I've optimized literal millions of dollars out of cloud expenses by choosing the best processors for my stack, and weeks later got myself schooled (on devRant, of all places!) over my ignorance of their inner workings. And I have a MSc degree. Learning never stops.
So, to improve CS experience in uni? Tear down students expectations, and boil out the "I just wanna code!" kiddies to boot camps. Some of them will be back to learn the science. The rest will peak at age 33.17 -
NEW 6 Programming Language 2k16
1. Go
Golang Programming Language from Google
Let's start a list of six best new programming language and with Go or also known by the name of Golang, Go is an open source programming language and developed by three employees of Google and the launch in 2009, very cool just 3 people.
Go originated and developed from the popular programming languages such as C and Java, which offers the advantages of compact notation and aims to keep the code simple and easy to read / understand. Go language designers, Robert Griesemer, Rob Pike and Ken Thompson, revealed that the complexity of C ++ into their main motivation.
This simple programming language that we successfully completed the most tasks simply by librariesstandar luggage. Combining the speed of pemrogramandinamis languages such as Python and to handalan of C / C ++, Go be the best tools for building 'High Volume of distributed systems'.
You need to know also know, as expressed by the CTO Tokopedia namely Mas Leon, Tokopedia will switch to GO-lang as the main foundation of his system. Horrified not?
eh not watch? try deh see in the video below:
[Embedyt] http://youtube.com/watch/...]
2. Swift
Swift Programming Language from Apple
Apple launched a programming language Swift ago at WWDC 2014 as a successor to the Objective-C. Designed to be simple as it is, Swift focus on speed and security.
Furthermore, in December 2015, Swift Apple became open source under the Apache license. Since its launch, Swift won eye and the community is growing well and has become one of the programming languages 'hottest' in the world.
Learning Swift make sure you get a brighter future and provide the ability to develop applications for the iOS ecosystem Apple is so vast.
Also Read: What to do to become a full-stack Developer?
3. Rust
Rust Programming Language from Mozilla
Developed by Mozilla in 2014 and then, and in StackOverflow's 2016 survey to the developer, Rust was selected as the most preferred programming language.
Rust was developed as an alternative to C ++ for Mozilla itself, which is referred to as a programming language that focus on "performance, parallelisation, and memory safety".
Rust was created from scratch and implement a modern programming language design. Its own programming language supported very well by many developers out there and libraries.
4. Julia
Julia Programming Language
Julia programming language designed to help mathematicians and data scientist. Called "a complete high-level and dynamic programming solution for technical computing".
Julia is slowly but surely increasing in terms of users and the average growth doubles every nine months. In the future, she will be seen as one of the "most expensive skill" in the finance industry.
5. Hack
Hack Programming Language from Facebook
Hack is another programming language developed by Facebook in 2014.
Social networking giant Facebook Hack develop and gaungkan as the best of their success. Facebook even migrate the entire system developed with PHP to Hack
Facebook also released an open source version of the programming language as part of HHVM runtime platform.
6. Scala
Scala Programming Language
Scala programming termasukbahasa actually relatively long compared to other languages in our list now. While one view of this programming language is relatively difficult to learn, but from the time you invest to learn Scala will not end up sad and disappointing.
The features are so complex gives you the ability to perform better code structure and oriented performance. Based programming language OOP (Object oriented programming) and functional providing the ability to write code that is capable of evolving. Created with the goal to design a "better Java", Scala became one behasa programming that is so needed in large enterprises.3 -
I'm a software developer. Last week I spent half a day teaching a "Senior Data Scientist" how to use git branches. I spent the other half a day teaching him how to use Jira. Now I'm being told that the dev team isn't raising enough Pull Requests. FML
-
I just came back from a meeting to a project that integrates some companies to achieve the project goals.
There was this "computer/data scientist" (his words) that every time he talked I just wanted to punch him in the throat.
Look, I'm not saying he isn't good or anything. He can be a fucking genius, I don't care.
But he talks as if he is the smartest person on the room, fucking annoying.2 -
Tldr; its a long introduction
Hi Ranters,
I've been on this app for quite a while now. As a shy cat watching from a distance and reading all kinds of rants. Anywho I feel comfortable enough to crawl out of my shell and introduce myself. Since I feel you guys together made such a pleasant and safe community, I'm really happy to be a part of it!
Anyway I'm Sam, 24 year old, from the Netherlands. My favorite color is green. Mostly the green you can find in nature. The one that calms you down:). I'm a very introverted person but always very curious and eager to learn new things.
I started to program when I was 12. I did assembly and C++. Because I liked making cheats for online games. Later I learned about C#, Java and Python. Mostly used it for web stuff, scraping, services etc. But also chatbots (for Skype for example).
Currently I'm 2 years in as a data scientist, mostly working in Python.
But on the side as a hobby and with an ambition I have a basic understanding of full stack development.
Mostly Nodejs, express, mongo, and frontend, no frameworks.
(I will later ask you guys some more questions about that! I could really use some advice!)
Anyway enough about me! Tell a bit about yourselves! Happy to get to know you all a little better!22 -
They think I'm a NASA scientist...
Yeah I mess with some data from curiosity, but I wouldn't say I'm a NASA scientist.3 -
Yesterday I met my cousins who are old enough to have kids. It was a good talk with them bringing back the old memories. One of my cousins has a barely 5 year old kid. I tried to talk to her and the conversation went like this:
Me: “hey there! Hi, how are you?”
She: “Good. What do you do?”
Me: “I am a computer science engineer. What do you wanna be when you grow up?”
She: “A scientist.”
Me: **thinking calmly, “Oh, what kind of scientist?”
She: “A Data Scientist.”
Me: **Two seconds of silence and decides to leave...4 -
Here is what I see in industry right now.
Don't go on math but get the gist.
1. 9 of 10 developers are Web developers
2. 9 in 10 developers want to be data scientist
3. 9 out of above actually give up and start doing Web development
4. 9 in 10 developers think CS education is not necessary.
5. 9 in 10 developers want to work for Google Facebook and Microsoft.
6. 9 in 10 developer don't make it to above companies.
7. 9 in 10 developers think design and test are important but never do it.
8. 9 out of 10 developers don't want to code after 5 years and just want to exit industry to non technical roles.
9. 9 out of 10 developers don't get rants and dev memes posted here.
What's your take on this7 -
So I finally got a job where I was an intern as a Data Scientist.
PS : I am a non-computer science background guy, who made it through.3 -
Corporation.
Meeting with middle level managers.
Me - data scientist, saying data science stuff, like what accuracy we have and what problems with performance we managed to solved.
Manager 1: Ok, but is this scrum?
Manager 2: No they're using kanban.
Manager 3: That's no good. We should be using DevOps, can we make it DevOps?
So yea, another great meeting I guess..4 -
Some of these things are not like the others. One of these people is a tv scientist not an actual data engineer or data scientist, while another is an activist and while is extremely respected, has no room in a data+ai talk -.-
10 -
Does anyone else here hate people who use numpy panda and tensorflow and call themselves data scientists ??
Cuz I hate 'em. There are so many researchers who work day and night to figure out the math and algos which go into these libraries. These researchers are real data scientists.
If computerss sciemce would have been a religion, then just using these stupid libraries and claiming you are a data scientist would be blasphemy.7 -
The everything is Data science craze trend.
Honestly it's not even sustainable with every kid and their grandmother wanting to be data scientists because it's a 'passion' and a 'dream job' and all of that click bait stuff.
It's just become ridiculous at this point and I doubt we'll even have the long awaited 'breakthroughs' people have been talking about for so long.
Also I have a strong feeling everyone thinks it's their 'passion' because it tops the lists of highest paid jobs out there and everyone thinks with 3 months of training they're a fully fledged data scientist because some Python or R package implements all the algorithms he could ever think of using.
Add to that the fact that most advertised data science jobs are actually data engineering where you maintain a date store and that's it.
Agree or disagree that's my piece and if you can convince me otherwise I'll be surprised because I've been subscribed to this idea for so long that it lost me some real good opportunities because I thought it was just what I was meant to be doing which turned to be false after I thought about it. There's a million other jobs that are more impactful and with pursuing.2 -
Comment a 1 if you’re a web dev.
Comment a 2 if you’re a game dev.
Comment a 3 if you’re a data scientist.
Comment a 4 if you’re in cyber security.
Comment a 5 if you’re in IT.
Comment a 6 if you don’t fit any of the above categories and you code only in PHP and refuse to learn any other language because you think PHP is the future.50 -
Another year is ending,slowly, without much of a hassle.
Here's to all those performers who are still waiting for the phone to ring, to all those students who thought they would be earning by the year end. Here's to that father who couldn't get his dying child to have one meal with him. Here's to that daughter who could not inform her imprisoned father that she has made it to the final. Here's to that 70 year old man who is still waiting for his son to return from the dead, to that 12 year old child whose parents just split up, to that girl who thought winter would be unbearable. Here's to that silent lover who is yet to tell the girl that he exists, to that girl whose new year text to her crush failed to yield more than a blue tick. Here's to that couple who had their child, to that scientist whose data sets are turning out to be promising, to that scholar who made it to the last of the Interview rounds.
Here's to that cancer patient who went into remission.
Here's to that boy who got a Hi message from his crush, to that girl who is getting married.
Here's to all those promises and resolutions. Once again. The ones we couldn't keep,and the ones we kept. Here's to that promise that our GPA shall rise again,that all the incomplete MOOC courses will someday be done.
Here's to the beauty of fantastic beasts, Star Wars, sense8, Westworld and all the films and TV shows that made us happy.
Here's to life that goes on. Uninterrupted. Fearless. Still.
Happy New Year2 -
So last week I really fucked up
I had this new implementation that was supposedly to be integrating smoothly into the rest of the service. It depended on a serialized model made by a data scientist. I test it in local, in QA environment: no problem.
So, Friday, 4pm, I decide to deploy to production. I check once from the app: the service throw an error. Panic attack, my chief is at my desk, we triy to understand what went wrong. I make calls with cUrls: no problem. Everything seems fine. I recheck from the app again: no problem.
We dedice to let it in prod, as the feature work. I go get some beers with the guys, to celebrate the deploy.
Fast-forward the next morning, 11am, my phone ring: it's a colleague of my chief. "Please check Slack, a client is trying to use the feature, it's broken"
FUUUUUUUUUUUUCK!!!
Panic attack again. I go to the computer, check the errors: two types of errors. One I can fix, the other from a missing package on the machine that the data guy used.
Needless to say, I had a fairly good weekend.
Lessons learned:
- make sure Dev, QA and Prod are exactly the same (use Ansible or Container)
- never deploy on a Friday afternoon if you don't have a quick way to revert1 -
Data scientist and related devs, how do you handle large datasets?
I was given a .txt file containing +1M edges of a directed graph. I tried to analyze it with networkx, but my computer killed the process as it was eating too much CPU/memory.
I would be grateful for any advice!23 -
Depressed since yesterday.
Updated all our clients Dialers. Stellar performance. Suddenly one of 15 can’t hang up three way calls.
It’s one of our biggest clients. And they just started. We upgraded the dialers so the answering machine detection would improve for them and it did, along with vast performance upgrades as well. Suddenly, this issue.
2 days in they pull the plug until we fix it. The issue is sporadic and we cannot reproduce. No one else is having the issue. I can’t even debug it properly as it’s a third party dialer with no customizations on it. I found out where the error is, but no idea the workflow they got it to happen with or why. It’s so frustrating. It happens using the dialer native interface, and our integration via api calls. The channel doesn’t get sent to the command for some random reason, and only sometimes.
So even if it’s fixed they don’t trust the system. Now they are losing the full integration we have with the crm and dialer and it’s going to be a mess of data for them. All because of this one issue. They love the CRM though...
If they had just stayed on one more day I’m sure I could have found it. Now I have to play forensic scientist and look through old data, without being able to see the client code that was causing the issue.
Just threw some cash down to be able to talk to the dialer engineers and hopefully see what’s up. What a nightmare. And I have so many other projects for the platform due so soon...
Sigh. Super depressing.1 -
My first rant here, I just found out about it, I don't have much of programming background, but it always triggeredmy intetest, currently I am learning many tools, my aim is to become a data scientist, I have done SAS, R, Python for it (not proficient yet though), also working on google cloud computing, database resources and going to start Machine Learning (Andrew Ng's Coursera).
Can anybody advice me, Am I doing it right or not.?2 -
Last week I got told by an incoming CTO, a week old to the organisation, that I'm good for nothing and unable to produce any work. He told me that he'll replace me and put me in a team where I'm more resourceful as I have been consistently underperforming. (He doesn't understand data science yet fyi) Then, he informed he's hiring 5 new teams members.
Me (junior data scientist) being really passionate about work was shook to hear this. So much so that it took me a week to even recover from it. I have considered counselling sessions too.
Week later, 5 new team members decide to flip his offer and not join. Another existing senior member decides to leave as well. Meanwhile, major issues in existing systems emerge and only I could solve the same. Still haven't heard back any from him though.
Is this the industry standard though ? Is this how CTOs normally function ? Throwing shit at people without knowing their value or valuing their efforts ? Especially with junior developers. It's only been 2 years in this profession and I've not met more than 3 genuine and helpful people. Maybe it's just my organization.9 -
Recruiters are driving me crazy, you can't even damn write a proper message with my name on it, no you just send 10000 messages a day and hope to get a response.
"""
Hey {firstname}
I am currently looking for a Lead Data Scientist in MyCity to work with a unicorn tech company.
You need strong Machine Learning Experience, be happy to be client facing.
Highly competitive package on offer.
Regards
"""
{firstname} T_T -
My image of dream career through different times of my life:
- frontend specs prodigy, css enlightenment, a member of w3c or a similar committee
- indie hacker and entrepreneur, leader of a startup community
- architecture prodigy, expert in scalability
- transsexual evangelist, popular article writer and a rockstar
- hardware engineer: Linux, C, chip and dale’s Gadget-like girlfriends, xkcd, latex, assembly, buying a radio station and a telescope
- scientist like NickyBones, papers, data, more data
- art expert
Though achieving one of this would take the entire life, I had a chance to grasp all of this. WHY does they feel so incompatible? Why do I have to choose?
Why do I feel so sad? Why do I feel like I haven’t achieved anything even though I objectively achieved what I dreamed of like five years ago?
Is it true that it’s in my nature to always seek an environment to feel like a junior in? Is feeling like a junior only pleasant to me because it reminds me of old times when I wasn’t actually this mentally ill and was still happy?
Why do I feel like that arduino and C shit is the equivalent of a red corvette?6 -
Data Science MSc instead of Computer Science. Or realising that my first 4 years of work was as a Data Scientist and I should have asked to have my job title reflect that. Skipping faang, at least relatively early in my career (that's a whole thing I want to write about but not rn). Not spending a year out of work due to health problems & nearly dying.
It could have been better, but I've enjoyed it.4 -
I just received this.
"I'm just saying that one should be proud to be able to import libraries and call themselves Data Scientist who can apply machine learning."
What the actual fuck.6 -
Packt.com (dev education books) is doing a survey of their readers. I don't fit into any of their boxes, closest one is data scientist.
I think I might really be a mathematician rather than a dev...
I hated maths at high-school.1 -
2018: Data Scientist = Stack overflow copy pasting: "I followed a 12-hour 'DS' course on Lynda!"
lm() # science2 -
Am I Data Engineer or Software Development Engineer ?
I design the infrastructure for analytics data, and I build the infra entirely including an development. Except making reports out of the data.
What I'm supposed to be called ?
Data Engineer ?
Software Development Engineer ?
Definitely not an Data Scientist. Official designation given by company is Data Engineer II. But what I'm ?
Confused, someone help me please.5 -
Lots of good suggestions up in here.
My personal prefference:
Such as there are governing bodies indiciating how a programming language evolves and a web consortium...there should be a computer science one. That dictates fundamental approaches covering everything that belongs to this wonderful branch of science. Everything from math to differenr scientific branches all the way down to turtles. And for it to be standarized and updated. Indeed, if you want to spend your entire existence gobbling js in the form of web sites then that is fine, but you should have sufficient knowledge to branch out into more academic pursuits if required.
Also, updated tools would be better, every aspiring computer scientist shall be able to navigate through all major operating systems and programming environments regardless of their beliefs and or prefferences and schools should provide said environments in their classrooms.
Data Strucrutes and Algorithms should be a must. Software engineering principles should be a must. Calculus, Algebra and Statistics as well as Physica should be a must.
And succesfully navigating over different engineering areas should be a must.
Not to cleanse the industry. Fuck your elitist mentality. If you think that programming is a sacred art that should exclude people then I really hope you fucking disapear from existence. No, not to cleanse. But to expand the industry and maybe show people that there is more than fucking around between node modules or gemsets.
Peace pendejos
**drops your mom's fatass...i mean mic** -
After a long year of going back to school for a masters. And working my ass off in networking events and internining. I can finally call myself a data scientist by job :D
-
SWE in fintech in MNC, job involves "bigdata' . Get paid >> avg
I FUCKING HATE IT. THIS PLACE IS A REAL DREAM-KILLER.
Size of the big-data ??? <50 GB ! Entire place runs on gimmicks and show off.
PO is a dumb cock sucker with minimal tech idea. He is busy sucking up business users and dictating us to rearrange tiles on reports all day long.
Fed up with all this shit , I decided to give GRE and apply for masters in Computer Vision .
For good GRE verbal score , I need to learn 1100 words , 90% of which I have never heard in my entire life.
WHAT THE ACTUAL FUCK ????????
Will my dream of working as a vision scientist for autonomous cars never come to life ???????
😢😢😢 😢😢😢😢😢😢😢😢😢😢😢
Plz motivate me to get out of this shit-hole -
Co-worker: "You don't need to know the math! Stop going on about it."
Me: "I think you do for some things, my algebra is not good at all, I need to improve it a lot and I just think you should too."
Co-worker: "Oh stop it, If the code runs it's OK!"
Me: "Well yeah, the code runs but you're over-fitting like a mad man and have a P-value of a bejillion."
Co-worker: "What!?"
"data scientist" -
me :: Musician a, Developer b => a -> b
This week I reached the end of a long journey and the start of the next one!
When I signed up here I shared a rant about where I was at the time:
https://devrant.com/rants/1279742/...
This week I accepted a decent salaried role as the leading Data Scientist in a well funded nonprofit organisation based close to my home! I’ll be the only technical professional in software development or analytics in the organisation and it’s a new role, so I imagine there’ll be a reasonable degree of flexibility in figuring things out and implementing them.
Have spent the last week (and will continue until my start date) building up a realistic collection of best practices while brushing up on tools they use (as well as tools and methodologies that I plan to bring with me).
After over a decade working as a self employed freelance, I’m looking forward to them change and to building out on different areas of my skillset!1 -
Met a newly recruited Data Scientist the other day and he complemented me on my work on information retrieval.
The lesson is keep learning, keep reading and keep trying -
We specified a very optimistic setup for a data science platform for a client....
Minimum one machine with a 16 core CPU with 64GB RAM to process data.....
Client's IT department: Best we can do is an 8 core 16GB server.
Literally what I have on my laptop.
Data scientist doesn't use any out-of-memory data processing framework, e.g. Dask, despite telling him it's the best way to be economical on memory; ipykernel kills the computation anyway because it runs out of memory.
Data scientist has a 64GB machine himself so he says it's fine.
Purpose of the server: rendered pointless.5 -
Today I had a full-day job interview for a junior data scientist position.
First I met the team which was only like half of everyone because apparently everyone was gone on Fridays. However the few there were really nice.
First task is to do some basic data analysis stuff even though I already spent a week on the coding challenge and sent them all my code/tasks. I log into my machine and create a new virtual environment but can't for the life of me figure out how to use the command line in windows to install packages. Turns out there is some problem with their proxy and they have to log me in on that. Then I am struggling on the keyboard because it's for a language different that my mother tongue and it takes me 3x as long to so the most simple things. All my shortcuts are out the window. Haven't a hard time typing parentheses and brackets. Start freaking out and have a panic attack mid task. I'm sweating bullets. I didn't even make it to the simple visualization tasks much less the models at the end. Time gets called and we all go to lunch and I'm freaking out on the inside the entire time. Angry at myself because I know I am better and just couldn't think.
After lunch I present my code and results from a coding challenge I did weeks prior. People from other teams get invited and I end up getting grilled for 2 hours by 15 people. Questions are flying in from all sides. They ask me almost everything I know about machine learning and some more. Under stress I forgot the name of the optimizer I used and couldn't answer some easy stuff because my mind was racing.
Right now I am on the train home and my body physically hurts. I am disappointed with myself and wish I could have shown up better. Never really froze up like this before.2 -
Hello
This is my situation:
Junior
Data Scientist
No working experience
From Latam
From Venezuela
Only allowed to work remotely
No work visa for USA or EU
Weeks looking for job, no luck, obviously.
Everything seems to be against me for land a job, at least a decent one. The other option is try to work in Upwork for 100 bucks implementing full pipelines, that is a joke.
Just sad.13 -
Welcome to post 2 of WHY WOULD I WANT TO WORK WITH YOU?, a saga of competence, empathy and me being dick, even tho I didn't want to be one.
This is a follow-up to: https://devrant.com/rants/2363374 It's title is: "Oh, you can post only every 2h. Didn't know that". I also didn't know that the rest of my rant would be put into a comment. For consistency tho, this time I am still splitting the story.
A wise person once wrote in their book: "People judge other people by two things: Empathy and competence." This may not be an accurate quote, but it carries the same message. Also, I don't really remember who was the author. I only know they were probably quite wise. Anyway, I just wanted to share that sentence. Have a moment and think about it. Or don't. Here's my story:
A was a software house that looked pretty promising. They were elegant, their page and offer looked nice. Well, unless you consider the fact that they offered me internship. Unpaid. But I decided to meet with them anyway, since I had hope that I could negotiate some sort of paid internship or a job contract even. I did my homework after all, and I was confident I am able to keep up with their requirements. I arrived a little bit... no, way to early. One damn hour. Whatever, I waited. I was greeted by a woman. We had a cultural conversation, she had a list of 12 questions I needed to answer, as a form of a test. We begun. First question: How do you change a value in Oracle Database? "Wait a minute", I thought, "What kind of question is that?". Why in seven hells would you want your frontend developer to know how to handle oracle db? Well, I gave my answer, I did lick some of that SQL in my life. Next question: Java stuff. The bloody gal didn't even care to check what position I am applying to before the interview! At this point I didn't really have very high hopes. A shame on them forever.
The story of B and C is connected and a little bit more complicated. More on that in part 2. B stands for Bank. A big corporation then, by definition. A person I know decided called me that day and told me they're hiring, that he referred me and that they would like to arrange a meeting. And so we did. It was couple of days before Christmas. C was a software house again. Or a startup. Idk really. Their website wasn't finished so I couldn't read anything useful up on them. They didn't tell me much about themselves either. They also started with "unpaid internship".
In C, they would greet me and instantly sit me down next to a mac laptop and told me, "hey, do this stuff in python". What the fuck, not again... I told them that I am frontend dev, they guy said "it's no problem, you said you know python, it's a simple task". And yeah, I did host some apps in Flask and I did use psycopg2. It was in my CV. But never, ever, have I mentioned knowing heuristics nor statistics. I'm no data scientist, monsieur. Whatever, I tried, I failed a little bit, I told them that maybe if I did want to spend half of my day there I would finish this task, but back then I was way too nervous to focus and code. I told them what should be done in code and that I just was unable to code this at the very moment. They nodded, we said goodbye and I was sure not to hear from them ever again.
In B, I was greeted by a senior frontend dev. He told me the recruiter is sick and he couldn't come, so we're talking alone. I can buy it. We sat down in said meeting room, and he asked me if I wanted a drink. No thx, I had digested so much caffeine during last 24h, next dose could be an overdose. And then, he took out my resume printed in paper. With notes on it. With some stuff encircled. That bloody bastard did his homework. We spent over an hour, just talking in friendly atmosphere. It was an interview, but it was a conversation also. We shared our experiences, opinions and it went just perfect.
On December 20, I was heading home for Christmas. My situation looked like this: A called me they could offer me only unpaid internship. I was getting kinda bored of rice and debts, tbh. I gracefully rejected their generous offer. B didn't give me feedback yet(it was a most recent interview, so I didn't expect any message until after Christmas anyway). C told me that they could give me internship, but I managed to convince them to make it paid internship. After three months of very bad times, things were starting to get better.
On part III we will explore further events of my very recent past. That post will be same amount of storytelling and possibly a lesson for those who seek an employer and for those who seek an employee.6 -
When you wanna be a Data Scientist and always land into internships where you are assigned with web development...
Learnt Node, Flask, Spring frameworks across different internshis... -
The gap of data science in industry and academia is so large. As a data scientist in a large financial company, I see that people are still using traditional models such as linear regression and SVM, while people in academia keep inventing new concepts and techniques such as deep learning.
I am not saying that we should completely embrace deep learning, or stick to classic methods. But I just feel so surprised that the gap is so large...Sometimes I am even thinking whether I am doing the right "data science"...3 -
So today in school I decided on my career choice. So I've decided on becoming a data scientist because I can still use my programming and I very much do like looking at data and researching things as well as program obviously :) so if there are any data scientists or data miners out there do you have advice?5
-
Opinion: Julia will not catch on, because the two language problem is not a big issue for most people in the industry, and most python data scientist will refuse to migrate.
-
The hype of Artificial Intelligence and Neutral Net gets me sick by the day.
We all know that the potential power of AI’s give stock prices a bump and bolster investor confidence. But too many companies are reluctant to address its very real limits. It has evidently become a taboo to discuss AI’s shortcomings and the limitations of machine learning, neural nets, and deep learning. However, if we want to strategically deploy these technologies in enterprises, we really need to talk about its weaknesses.
AI lacks common sense. AI may be able to recognize that within a photo, there’s a man on a horse. But it probably won’t appreciate that the figures are actually a bronze sculpture of a man on a horse, not an actual man on an actual horse.
Let's consider the lesson offered by Margaret Mitchell, a research scientist at Google. Mitchell helps develop computers that can communicate about what they see and understand. As she feeds images and data to AIs, she asks them questions about what they “see.” In one case, Mitchell fed an AI lots of input about fun things and activities. When Mitchell showed the AI an image of a koala bear, it said, “Cute creature!” But when she showed the AI a picture of a house violently burning down, the AI exclaimed, “That’s awesome!”
The AI selected this response due to the orange and red colors it scanned in the photo; these fiery tones were frequently associated with positive responses in the AI’s input data set. It’s stories like these that demonstrate AI’s inevitable gaps, blind spots, and complete lack of common sense.
AI is data-hungry and brittle. Neural nets require far too much data to match human intellects. In most cases, they require thousands or millions of examples to learn from. Worse still, each time you need to recognize a new type of item, you have to start from scratch.
Algorithmic problem-solving is also severely hampered by the quality of data it’s fed. If an AI hasn’t been explicitly told how to answer a question, it can’t reason it out. It cannot respond to an unexpected change if it hasn’t been programmed to anticipate it.
Today’s business world is filled with disruptions and events—from physical to economic to political—and these disruptions require interpretation and flexibility. Algorithms alone cannot handle that.
"AI lacks intuition". Humans use intuition to navigate the physical world. When you pivot and swing to hit a tennis ball or step off a sidewalk to cross the street, you do so without a thought—things that would require a robot so much processing power that it’s almost inconceivable that we would engineer them.
Algorithms get trapped in local optima. When assigned a task, a computer program may find solutions that are close by in the search process—known as the local optimum—but fail to find the best of all possible solutions. Finding the best global solution would require understanding context and changing context, or thinking creatively about the problem and potential solutions. Humans can do that. They can connect seemingly disparate concepts and come up with out-of-the-box thinking that solves problems in novel ways. AI cannot.
"AI can’t explain itself". AI may come up with the right answers, but even researchers who train AI systems often do not understand how an algorithm reached a specific conclusion. This is very problematic when AI is used in the context of medical diagnoses, for example, or in any environment where decisions have non-trivial consequences. What the algorithm has “learned” remains a mystery to everyone. Even if the AI is right, people will not trust its analytical output.
Artificial Intelligence offers tremendous opportunities and capabilities but it can’t see the world as we humans do. All we need do is work on its weaknesses and have them sorted out rather than have it overly hyped with make-believes and ignore its limitations in plain sight.
Ref: https://thriveglobal.com/stories/...6 -
Working with a data scientist on an update to a machine learning api that has dinner logic change with a new model.
He's wondering why his PRs are falling.
He's trying to merge into development from a branch created off of main.
He's renamed all the functions and classes and never updated the call points.
He's using new packages but never includes them in the requirements file, so the docket builds are failing.
His class method definitions don't contain self and are throwing syntax errors.
I've been working with him for 4 days to get him to understand branching, linting, unit testing, and not blindly copy and pasting snippets from jupyter notebook into production api code!8 -
Data scientist life begins when for him:
Forest becomes Random Forest and Tree becomes a Decision tree.
1 -
I work as a data engineer in my company. My senior calls himself data scientist- he is 29 years old and recently did one MOOC on data science!
I wonder when my colleagues will find out about how much he really knows.
Till then I am cleaning and arranging his data, while he sits and earns a big fat package by citing one data scientist tag to his profile!! -_-1 -
I decide to study Data Science the last 10 months, right now im very competent and have the skills get hands on real projects.
a few months ago i meet a guy on LinkedIn, i help him with some task for some stuff he was doing.
a few weeks ago he say he will hire me for work on an startup he is running with other guys.
after that he never get back to me and not get any response to my messages. i dont know what i do wrong.
now im here feeling cold and dont even know what todo for get some remote work as data scientist.
feels bad bruh :"( give me some directions, where to look for Remote Junior Data Scientist Job?9 -
Got in contact with a company in July about a job. Had an email this morning about arranging a call with the CTO next week, so I've progressed to round 2 of interviews in... 4 months? I had just started my current role in July, so no rush. Have had a few chats on and off, but silent for a month.
I don't mind, I've had health stuff dominating my time, and might be a straight data scientist job title, which would be awesome, but... 4 months? There's at least a couple more rounds after this, so may well have been at my current role a year by the time I get an offer! -
This type of data scientist are the worst of them all. The lesson he is giving on this ost is, "I am great." But keep a look at his post, he have not even followed basic syntax rule.
3 -
Data Scientist: Recommendation Engine
Sr. Data Scientist: Machine Learning system to recommend personalized content to users.
Principal Research Scientist: AI to realise users' need for content and customise the user feed using content populated for maximum content usage that correlates with their likes/needs/wants.
God: ... -
Context: I am leaving my company to work at a data science lab in another one.
My senior dev (with PO hat): we need to gather data from prod to check test coverage. You will like it as you will be data scientist hehehe (actually not funny). You will have to analyze the features, and find relations between them to be able to compare with the existing tests
Me: oh cool, we can use ML to do that!
Him: Nope, we need to di it in the next 3 weeks so we need to do it manually.
Me:... I have quit for something.... -
everyone needs to be a data scientist/evangelist/superhero or AI enthusiast/developer/super-coder or project head for critical business needs/ or doing analytical analysis for business processes...even school students who are learning just to write English sentences, think they can code easily
AI folks, who think you can code automatically by thinking with no typing..
to them i say
2 -
I want to become a data scientist and am now making an Android app to collect data from people. Am I doing this right? Idk wtf I'm doing anymore x(1
-
Hey guys i need help, i want to switch to data field from react, i hv 2 yrs exp in react, should i go for data science? Can a frontend guy like me become a data scientist? And is the data science job fun when compared to react? Or should i go for power bi developer? I heard that power bi has a lot of scope as well. Thanks
Top Tags
Weekly Rant
View