Related Posts
Conversation Starter
Any one here from magneti marelli account?
NYC 🐠 Anyone try the dating app MOTTO? Any good?
Enthusiast
And the rest is history 😅
Additional Posts in Data & Analytics Consultants
today I choose violence
Subject Expert
Mentor
Community Builder
New to Fishbowl?
Download the Fishbowl app to
unlock all discussions on Fishbowl.
unlock all discussions on Fishbowl.
As long as the pay is good - sit back and enjoy. You hit the jackpot and now live on easy street. If you need to keep your skills sharp in the mean time side projects are the way to go. Alternatively, you could come up with MVPs or proof of concepts for things you think will help your company to try to move up faster but YMMV
If you hate a job, change it. Whether that means a job elsewhere or creating new work here is up to you.
Bait and switch. Happened to me at my last gig and quit after 8 months
Thats how most roles are. If you want to completely replace the excel with python, it'll also end up requiring even more sql and more care for the sql you write.
Btw, the python won't be exciting either. 80-90% of it would be copy pasting boilerplate snippets of airflow, etc. Definitely way more interesting than excel imo since having to actually think about data flow adds a dimension, but functionally it would be more or less the same role but with more work on pipelines.
ThisZ
My dude I don't think anyone does data "science" outside a few firms. Based on people my age my read is that 80% of value is in the simple analytics that requires boring SQL or boring python or boring excel, interpretation is the only rewarding bit.
Fancy ML and modelling is super crucial for select fields and firms but for most industries it's a good to have.
You just explained why no one wants to be a ‘data scientist’ anymore
This is way too common I hear
Quick comment - whether you stay or go up to you. Take advantage of your time to totally master SQL. Value is very often overlooked. Can’t tell you how often SQL has come to my rescue when needing to mine nasty disorganized databases for a feature set to model
HRs have caught on the buzzword that is Data Science. There are countless people this happens to (myself included). As long as they continue a data scientist wage while doing entry level analytics work, I’m okay with it.
Ask up front of it's product analytics or ML, then ask about the stack. Very easy to distinguish teams that have actual ML happening from those that don't this way.
If the role isn’t as described and the WLB is terrible, then that is a very explainable story on your resume when interviewing elsewhere (assuming you don’t have a string of short roles). I’d look elsewhere rather than be miserable and lose the skills you currently have. Try talking to “peers on the team” when you interview and ask questions about day in the life and tools, methods, etc and you’ll hopefully catch this in advance next time.
Feel free to lie on your resume about your responsibilities when applying for other jobs, as long as you can do those things. I can relate to your circumstances because I am in a similar position. These stupid companies face no consequences and get away with things like this.
Sounds like you’re doing data engineering. Without a good foundation of developing the infrastructure acquiring and maintaining the right clean data, good ML isn’t sustainable.
Look for a new job unfortunately. I worry about this happening to me as well. At the cost of looking like a crazy candidate, I usually ask the same question to different people on the panel to get a better idea of WLB, type of work, etc
Y’all hiring? Lol
I recommend switching roles or companies. If you plan on moving up in the DS field by going to larger companies, they’re going to pass you up if you don’t have advanced DS skills that are not what you described. They’ll want to see modeling, hypothesis testing, data analysis, and it won’t be great if all you can speak on is SQL
BI/Data Analyst is your home my friend.
Welcome to data science :)
And I don't even mean that in a negative way. Let's be honest, the combination of curiosity, domain expertise, intuition, and SQL can be incredibly powerful. Can also get great answers faster than it can take to build the perfect model, etc. And can give you fantastic features to feed into your models if the use case calls for a model.
Doubt you'll ever fully be away from SQL etc. I have yet to see it, except for people who actively avoid using it (i.e. avoided when it was obvious it was beneficial to use, people who push all DE tasks to data engineers).
I don't do data science but I do those things you mentioned. I'll swap in if the TC is right