I’m seeing many resignations on LinkedIn following the selections.
I’m seeing teams recruiting externally for data scientists after layoffs.
I’m hearing of unqualified people, with no background in data science, being given positions, whilst others are let go.
I’m hearing that AI has been moved under CNE?!
WTAF?
@cq all those IT middle managers that you speak ill of are now putting AI/ML project management experience in their LinkedIn profiles because it’s the thing to do. Unfortunately we can’t challenge their claims.
@p1 because it is a tight-knit community in the US, and everyone tells each other what they’re doing.
Also, the ones who EOI’d were mostly San Ramon. Very few Houston people elected to leave even though they were job hunting. The timing didn’t work out, but many eventually left on their own. Like others said, everybody who wanted a job did land a job with the exception of 1-2 people.
@nx which platform? And how do you know who was left standing vs EOI’d?
@kb there was literally only 1 DS who didn’t land a position, so yes, I guess you are. Or you’re just trolling.
@ka damn, that's ice cold. I must have been pretty terrible then.
@jn another d-mbo confusing data engineering roles with data science and ML engineering roles. No good DSA got laid off. Everyone had a box. The ones who left chose to leave. Most without severance since not many EOI.
They let good ones leave / laid them off while retained mediocre / downright underqualified folks. For Pete’s sake, there’s MBAs in data engineer transition roles who don’t know what a for loop is. Take a look around; you’ll be severely unimpressed. What a joke all of IT has become. Oh well. Enjoy!
@dk the fact that digital scholars got mixed in with the same thread as data science just shows how d-mb company is in confounding the two. At any rate, the jokes on them. Locked into that company for 5 years with no chance of career progression because they can’t really quit.
@cs There’s a ridiculous entitlement with digital scholars who have no clue what they’re doing- just took a few classes and think they know what they’re doing. No one looks at their results
@cp you’re giving LC too much credit. The id--t tu-d who single handedly destroyed DS was none other than Ranjan who someone failed upwards into working side by side with ELP ES and AS. ENGINE is a disaster that they won’t recover from. It’s too bad. That was a good group, but it was time to move on as the writing was on the wall with the leadership direction
@bd the digital scholars program is a huge failure. A bunch of entitled a--holes who are ungrateful for the job they have while others are being laid off.
@c9 hide the AI budget? Gimme a break. The AI budget is a fraction of the IT cost. 0.1% of the total IT budget last year.
Ever since Chevron moved to the braindead platform model and having the useless PLMs trying to manage data science work, it was the beginning of the end of DSA. It was kind of a slow death. The people stuck around for 5 years because they at least had a semblance of a community. I heard through the grapevine that the DS leader advocated for moving everyone to the AI org and leave no one behind, but that was rejected by LC. Now you have people exiting the company left and right, while the enterprise AI group has seen basically no attrition except maybe some San Ramon people who didn’t want to move. Putting a bunch of DS/ML people who know the business fairly well under IT middle managers who don’t know anything beyond ADO reporting is pretty much the third d-mbest thing IT has done, right behind triple crown and engine when you already had Manila and BA.
MN and LC ki-led data science in Chevron.
AI moving under JG is just to save what’s left of it because LC has no clue.
LC destroyed data science at General Motors before he joined Chevron, too. Same playbook. Same outstanding results.
AI moving under CNE is solely to hide its budget and obscure where the money is coming from / going to. Zero to do with to any kind of leadership focus or technical reason.
Pretty much all of the people who could actually do (and did) data science, particularly those with an actual subject matter expertise in things like petroleum engineering, process engineering etc., left Chevron already. It turns out that people who are good at spotting patterns were able to spot the sinking ship.
The DSDP and data science challenge were fun, engaging, and great for networking. At least they were trying to develop employees. Too bad - if they create an AIDP now, it would be the Ashore India Development Program.
Data science has been toast for a while. First, there’s no real work to be done so why would you need it? Second, management is stupid in that they don’t understand how to leverage this particular skill. Third, if you do really need a model or something, just ship it off to India!
Seems like a waste to train up all those rice and mit fellows people, but this company will waste a billion and not even blink an eye.
AI is only as good as the people using it. Stupid questions in, stupid questions out.
AI is everywhere…