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Bowl Leader
Anyone else moon lighting here ?
Curious to know if you've legitimately declared it to your core job peers and if yes how are you balancing ?
What I know is if i can be a manager at a regular office and yet have my own start up venture(s) on various other skills, it shouldn't ideally conflict but some HR do poke in between
Anyone from Accenture India ?
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Bowl Leader
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
Mentor
Has anyone else begun to resent data science?
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This is funny because I’m actually on a data science project with Deloitte currently and am having the time of my life.
No ML or DL? You're a wannabe. Not using Databricks? Well get lost son. Nice try.
I will say it is challenging to find a data science project, but they are out there.
I joined Deloitte in a management role for DS and left because its not a good DS firm. There is talent in the firm at a junior level here. The issue is senior level and lack of or quality of projects.
Most of the projects in this space are either staff aug or fairly simplistic work a true DS would not want to do long term. A lot of the leadership are strategy folks who do not have the technical capability. They have their sales decks and are able to put forward ambitious plans for where clients should be in terms of data integration, use cases and so on. They just dont know how to implement it. So they sell first stage projects like we can show you how to bring these data sources together and build a model plus dashboard. Then the client takes it on themselves and it never progresses because Deloittes way too expensive for this kind of work. Other times they claim to have a tool/service that is advanced and industry leading. Its often not close to that but they do a great job hyping themselves up into believing it.
At the more senior level you run into politics. Partners selling whatever they can and find an SM who is their go-to for doing the leg work, ie the deck. That SM then does whatever they can to box out anyone, M or SM, that may be a threat to encroach on this work. They need to hit their sales numbers and make PMD so can’t have someone else get in the way. So when we do hire M/SM who are technically sound, they often get pushed out by these strategy/sales people.
What about mbb or the rest of big4 ? You’d still choose Accenture above all ?
Can you provide names for smaller shops?
Yes I would love this too
This is very subjective. I’ve been working on data science projects for years now and have had the pleasure of working with bright data scientists and doing great work. Deloitte is huge and everything varies project to project, but a blanket statement like this is erroneous.
It’s not erroneous when you consider the 80/20 percent rule. Did not say Deloitte does not have data science projects. I said not the best place for deep technical folks trying to deploy the best data science work.
I think there's truth to everything being said here.
But the constant nerd flexing of 'thats not real data science!!!' is extremely tiresome, not to mention divisive and exclusionary. And if you are a "real DS" do you really need to be surrounded by other such data scientists to do your job?
Of course D is going to hype things up if it will boost sales. To someone considering D, I would suggest considering the whole picture - the networking opportunities, the compensation, benefits and Wlb compared to your other options, etc. I do agree that management can be rather clueless or indifferent to issues of quality, but sometimes the client doesn't need hardcore ML.
If you want to do hardcore DS at D, there are opportunities, you'll just have to be more discerning in looking beyond the DS label.
Worst comes to worst, being the one eyed man in the land of the blind isn't always a bad thing, you can work it to your advantage to climb faster.
Calling out “fake” data scientists is a necessary evil because they dilute the brand value of data science
It depends on the project. Agreed for the most part, but there are projects that can be conducive to learning.
Coach
I became a data scientist at Deloitte. Mostly I was self-taught, but there were a couple of really good people I worked with there. You do have to make your own path, but the nice thing is that because they don't know how to hire data scientists, you can get hired with less experience, so if you can be self-motivated, there are opportunities. It's not necessarily what I'd recommend, and the people I knew who were good technically left, but there is a advantage from the average level of technical competence being so low.
Ds1- Love your spirit! Not everyone at the early stage of their careeer can pull it off
My partner is trying to break in to data science/ analytics after being a teacher. She would happily come be a “wannabe” if anyone has a connection here
Ping me
i was hired as a data scientist 2 months ago and used python on my technical project and the specialist leader was honest with me during the interview. he said most of the work is in the exploratory data analysis stage.
What is a real data engineer vs a wannabe? Asking for myself lol. I started an data engineering engagement 11 months and feel like I’ve grown tons becuz I coming in in only knew SQL and Tableau. Since I’ve learned how to ETL and then automate any process/pipeline from source to dashboard using Python. Am I a wanna be lol? Again, asking for myself.
Coach
I mean, that sounds like data engineering. What's your stack?
The issue I think is that either the client will only take the proposal seriously if the firm adds a Data Scientist in the project, even though the project scope and deliverables doesn't require one, or the firm believes it can only win if the role is in the proposal, the client could care less. Either way, you may end up doing some data analytics, clening up data, nothing too sophisticated.
Any of you data peeps hear of Celonis? it is the tool we work with in the Center for Process Bionics. It is a data platform around Process Mining. It has components of data engineering, Business Intelligence, and Machine Learning.
I encountered the same thing on a few Accenture data engineering projects. They were SQL / data viz focused with no other language (see link below). I had a rude awakening when I applied to data engineering roles in tech and was told to apply for data analyst roles. (I was offended at the time because data analyst was a level at Accenture while data analyst is a role in tech lol). I eventually broke into tech after several months of self learning Python, spark, AWS, etc.
https://www.jesse-anderson.com/2018/06/the-two-types-of-data-engineering/
Would you mind to share some more details on the experience/expectation?
This statement could be geography specific and because the author was placed in wrong projects ?
I have a masters degree in analytics and experience working with Python, Power BI on previous projects. Looking for a data science project in the early June timeframe. Does anyone have any leads?
I’m open to it depending on certain factors. Which company is this for?
Get out and go to tech. Trust me.
Anywhere specific you recommend ?
Yupp. I can back this up
Honestly I maybe biased but check out Accenture!