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Is the CFE pretty easy?
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Mr Bean ❤️

Hello everyone, I am Data Engineer with skills on Azure and am holding couple of offers KPMG Digital Lighthouse as Consultant : 12.5 LPA fixed +20% variable +1.25L bonus Tiger Analytics as SE : 14.5 fixed YOE : 4.1 years Can you please help me with which is better in terms of growth and WLB with your insights ? Tata Consultancy KPMG India Tiger Analytics KPMG Deloitte EY
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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
today I choose violence

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If you really want to add a valuable skill, learn how to apply critical thinking to the datasets you’re analyzing. Far too many people in this industry focus on the technology, and far too few focus on the quality and validity of the underlying data (which is the truly valuable part of the whole process).
You’d be surprised how few people exercise it though.
Python or R will be useful. Also recommend Tableau as it tends to be more popular across healthcare. Always learn Excel. Learn basic stats and when to use certain kinds of tests / analyses.
Python and SQL. Know how to deploy custom models in Epic’s Nebula platform. Excel still comes in handy.
Lots of SQL. We work with Databricks, so for the non-SQL stuff, R and Python are pretty much interchangeable and you only really need to know one or the other
Is there a lot of demand in the big 4 for experience/certs in databricks?
Can speak from past internships and also client work in healthcare.
It’s a lot of Python and SQL for sure, but many places are still using SAS. Cloud infrastructure is definitely on the rise. With that, Spark/PySpark would be good to know as cloud computing is increasing its utilization.
BI skills and visualization I’d say are also good, depending on the job requirements. Maintaining and creating dashboards and putting together a visually excellent and informative decks are excellent skills.
Some healthcare data analysts and data scientists could be a lot more research-oriented, so core statistical skills, being able to perform categorical and continuous data analysis, proper experiment design, survival analysis. And coding with SAS or R or Python would be all applicable (although I love R and I will fight anyone about it)
From a technical skill standpoint, SQL and Python; SQL for pre-processing and data wrangling of large datasets and Python for basic ML modelling