Is there any advantage for being in "data analytics" versus becoming a "data scientist"? I'm a business guy who has self-taught myself how to code by automating processes in my previous consulting roles and shifted to analytics. I feel like I'm reaching a dead-end from a comp-perspective, however, because my job is mostly ETL using Python/PBI and then creating presentations to stakeholders on what to do. I feel like I need to pivot to DS to make real money ($250K)+. Thoughts on this?

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Really depends on the DS job you’re looking at. It’s not as diluted as Data Analyst but there are certainly very large differences between some DS jobs.

They do tend to make more money, but if you aren’t fully aware of the statistical math behind Machine Learning, regression etc. then you aren’t likely to land those jobs. For my current job I was asked to explain what can cause overfitting, Python code questions, suggesting ML Models and a riddle for the tech screen.

I’ve also had an interview where I was asked how I would analyze Survey results. Also at manager or above, you can get away with a more fundamental understanding for some employers.

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What industry are you in?

If you want to pivot into DS, you will need to do a lot of studying. DS involves understanding statistics, probability, machine learning, optimization, and a lot more technical topics. You can try breaking into the field with your current experience but just know you’re competing against data scientists who likely have at least some knowledge and experience in this. Roles that pay $250K will have you doing a lot more than ETL and automation.

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Label yourself as a data scientist if possible. It’s just a title and I’ve seen a lot of data scientists be more like analysts, but it’s more attractive.

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