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I joined Cognizant recently, the project interview calls which I am getting is not from my base location.
I have the location constraint, should I wait for the right opportunity or raise this concern to ADP team so they can look in to it?
As per ADP policy, one should not have any constraints and take the project as FCFS basis.
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Hi, I need a referral for an internship
in Financial Advisory Team
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can anyone help me?
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Additional Posts in Data & Analytics Consultants
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.
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
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What are your long term goals? DE is more akin to the computer scientist and SWEs while DS is focused on statistics and optimization. If you enjoy designing data systems then DE is better, but if you like hypothesizing and experimenting, DS will be better.
Also consider the industry you work in and the types of problems your clients need you to solve. My hypothesis is over the next 5 to 10 years, the scarcity of data scientists will wane as tools become more easier for business users. There will always be a need for data scientists, just in more niche areas like military applications, healthcare.
Meanwhile, I can’t imagine demand for data engineering will decrease as the starting point is always getting data.
I chose to lean in more towards DSci while utilizing all of my past skills with data engineering (Hadoop, Spark, DevOps, etc.). So my niche where I find my roles is “productionalizing and improving models”
Depends on what you like. I think If you prefer to do more data modeling and bring all the different data together then data engineering but if you prefer to do statistic analytics and predictive modeling then data science. That’s just from my experience though.
Anyone know a good boot camp to learn data scientist that’s not too expensive?
The first question is really whether you should go to a bootcamp or not. Are you just wanting to get on projects that are DS related or transition internally? What are your goals?