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Deloitte audit Vs. Grant Thornton Tax. I have an offer from Grant Thornton and From Deloitte as an Intern this summer. Deloitte is the bigger name and pays a bit better but Grant Thronton has way nicer people and known to have a way better cultre and work environment. What should I do? Where should I go?Deloitte Grant Thornton
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Thought this was interesting. Across 160 teams of researchers, just about all failed to make good life outcome predictions on things like GPA, evictions, layoffs, and others. Data followed 4.5k families across 15 years, with 13k features (varied over time). Haven't looked at it directly yet, but will be turning the docs and data inside out... In the meantime, authors claim this as showing the limits of ML. Oh, and it's published in PNAS, so you know there's some big publication energy there.
https://www.pnas.org/content/117/15/8398
What is a data lake in basic terms?
Got messaged by a C3 . ai recruiter. Read that wlb is bad and that the interview process is absurdly long, but the Glassdoor reviews are 4.2 and can't find actual hours worked posted by anyone. How's the culture really? I'd be aiming for DS consulting, something more functional but with DS/ML concepts as my differentiator.
C3.ai, Inc.
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Data science in consulting will never be true data science because budget hinders innovation.
I had a discussion yesterday with a bunch of clueless folks who asked me to share code for t-testing instead of putting together a document educating people about t-tests.
The thing is t-tests are a line of code. The real question is: do you know what to put in the parameters? If you think about it: this applies to most ML packages too. Anyone can say the word “automate”, but one still needs the underlying knowledge.
Data science has “no future” because it is high in demand and people are easily pivoting into any role they want after mastering data science. It’s also the place closest to innovation because of how it can be applied to the betterment of .. anything: supply chain, tech, advertising.. you name it.
Its going to change, but Data Science is just the latest name for the statistics and number crunching discipline that had existed many years now. It will probably evolve and change but you still need people who can read, understand, and apply statistics
I think if you're really committed to a particular technology and set of things you want to do, that might not exist, or exist at your current salary. But having a combination of coding skills, statistical knowledge, and ability to think about business issues/talk to people who aren't technical/etc. is still valuable even if no-code really expands or we can otherwise automate a lot.
Absolutely, the idea of a unicorn data scientist SHOULD die because it’s a poor model. The industry is evolving towards specializations.
I build machine learning models to model credit risk and monitor outliers in data (again, via ML models). My subject matter expertise is econometrics. I’m not titled “data scientist” though, I’m a quantitative financial analyst. This is well defined in finance because DS in finance is pretty mature. The rest of the world is catching up- fewer “data scientist” roles, more “adaptive marketing engineer” roles. It’s data science, but the problem space is significantly more defined than it once was.
Partially correct, working in the Data Science field in consulting firm is no future. I’m trying to get out now. It’s prestigious & lot of growth in the industry
…. So leet code and get in? It’s honestly not hard
Yes, data science is slowly dying out, in my experience. I started noticing this a year or two ago and started making the pivot to a ML Engineer role. Data science work is cool but the fact that most data scientists have to rely on a DevOps team, coordinating work with cloud engineers, etc. makes them just okay employees. What most places seem to be looking for now is someone who can write a model and actually get it working in production (something like a Full Stack Data Scientist).
Data science is not just machine learning engineering, there is so much value that is created without getting into production. So many organizations are far from production because they are still figuring out where investment is needed. It’s about $$$$ value not how sexy your model version is going to be
Hello I just got certified as a data analyst anywhere is hiring for remote work permanently?