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What is wrong with people these days?
Is it SAFE joining Wipro as technical lead (B3) with 37LPA? Knowing that package is pretty high as compared to collogues in same band. HR is not ready to give project manager(C1) position.
Appreciate your suggestions/input.
Would there be any scope of increment going forward?
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Wipro Infosys HCL Technologies Tata Consultancy Cognizant
Leaving this here
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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.
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Starting off with data viz and eventually moving to data engineering….
I think data viz helps you become a better consultant than backend stuff because you are more client facing and dealing more with stakeholders.
However, I think if you want to become more technical than database/pipeline and SQL would better prep you for that.
Don’t do data viz if you want to become a data scientist. Data viz people get stuck doing data viz
Not true! I started out with data viz using Qlik Sense. Heck I was even certified Qlik dev but I’m doing data architect now (E2E)
Just curious, how is the market for Qliksense? I see Power BI and Tableau everywhere. Some companies use Microstrategy.
Not big but Qlik Sense is a powerful tool when it comes to enterprise capability and data volume!
SQL and in depth Python skills are essential to your career.
Data viz basics are important to your career, but that's the extent.
Qlik doesn't matter at all unless it becomes your thing and all you do.
Seems like you have a good opportunity here
1. Learn Qlik (viz and data model ‘qvd’) - this will help you build your story telling skills. You’ll need it as a Data Scientist. I’ve worked with DS who only builds models but unable to tell a story with what they built
2. Learn some data engineering works so you don’t have to wait for DE to build pipeline for you or you can understand what they’re doing and make them build the pipeline the way you want it. Think MLOps.
3. Try to understand the architecture as well. This will help you identifying performance improvement. A model can run fast with computing power but can be slow to serving if the architecture sucks.
Hmm, I think you need to be a little more specific about what activities/tasks you want to perform at work rather than focusing on title. DA and DS are pretty similar roles these days, DS might be more exploratory and less dashboarding. True model building seems to be work for those with the title research scientist these days. DE will help you build CS and Networking/DevOps skills, especially if it’s not just writing SQL in a database system. Can you expand on what it is you want to do as a DS?
Very good point, depending on the organization the roles are similar and I shouldn't focus on just a title.
As a DS my goals would be to build my coding skills, not just SQL but increase my Python abilities. Additionally, I want to learn not how to build models, but to utilize already established ML models to provide the most value for whatever business problem I come across. Whether it be time series analysis, A/B testing, random forest etc. Then convey that process to stakeholders to demonstrate why the insights I provide can solve whatever problem they have. I'm eager to continue learning and advancing in my DS career technically because I never thought I'd be able to, I just started in the tech field from a non-traditional background.