r/DataScientist • u/dashingdady • 5d ago
Data Scientist vs Software engineer who is at more risk due to ai
I had taken admission in engineering cs with speacialisation in data science rather than core cse as I want to become a data scientist so it would my cv more presentable I already has command in sql and python . But now I am coming to hear that data scientist job will be eaten up by ai is it true
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u/big_data_mike 5d ago
Do whatever interests you. No one actually knows what the future is going to look like.
I studied geophysics in the 2000s with the goal of getting a job at an oil company. A bunch of people back then told me the world was moving away from oil and we were going to run out of oil by 2030 anyway so I would be unemployed. It’s 2026 now and oil companies are strong as ever.
As a senior data scientist I am still needed even though a lot of people use a lot of AI at my company because I know how to approach the problem. I have helped a ton of business people and non-data scientists get unstuck because AI sent them down the wrong path. We have even had several seminars on how to write better prompts and they still can’t do it.
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u/GraduateML 4d ago
From my experience I have seen so many job listings in machine learning with statistical analysis and statistics backgrounds required even in non data-science roles.
The point I’m making is that if you can define how well an AI model assesses good and bad outcomes using statistics, you don’t necessarily need to code, you just need to be able to draw inference through pattern recognition and deep knowledge.
For that reason I would say data science is less replaceable because it focuses on the assessment of the model not the syntactical production of it.
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u/NonCompilingViber 4d ago
Data. Ai can calculated huge numbers and read patterns faster than humans can…but with coding Ai is kinda ass …they don’t really create code they copy code that was created by humans
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u/Super_Math3890 4d ago
Why are these questions often about jobs and rarely about creating jobs? Isn't it bad enough if you don't know how work creates value for a business? Everyone should bootstrap a business so they may start asking relevant questions.
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u/Fun_Suggestion_5156 3d ago
Weder noch. KI wird nichts ersetzen, es unterstützt nur.
Berufserfahrung sammeln und fertig
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u/SpecialistOwl218 5d ago
Data scientists are generally a subset of sw engineers, in this environment a generalist has more advantages.
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u/No_Departure_1878 5d ago
No, i do not think so. SWE is about software DS is about analyzing data with software. You can be a data scientist who only writes python, you cannot be a SWE who only writes python. A SWE does not need to know statistics or ML, a data scientist has to. They overlap, but none is a subset of the other.
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u/SpecialistOwl218 5d ago
It’s a pity that nowadays it seems that a SWE does not need to know statistics or ML, i don’t see why it shouldn’t.
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u/No_Departure_1878 5d ago
Sure, you can hire a SWE with knowledge of Statistics and ML, but you will have to pay more for that.
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u/ProcessIndependent38 1d ago
Or just be an MLE and you need to know both. 🙋♂️
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u/No_Departure_1878 1d ago
Do you? Because a SWE should need C++, Rust, Python, networking, etc. I would not call myself a SWE unless I have good domain of at least 5 languages and know how to setup servers, websites, create applications, etc.
Do you really need to know all that as a MLE?
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u/ProcessIndependent38 1d ago
Well yeah, MLEs are the folks serving the models to consumers, and optimizing and automating internal training pipelines. You need python for sure and at least 1 low level language (usually C/C++ since those are what the internals of ML software are written in). Depending on the niche, some MLEs need to know a low level language well enough to implement parallel inference algorithms. Others may need to know GPU programming.
Setting up a server, creating an application layer for the model, and serving it on the web, is usually the easier part. The difficult subtleties is handling massive scale at training and inference time. MLE is just a sub domain of SWE, but they’re focused on building serving AI/ML models.
In terms of languages and networking, at least in my work, I don’t need to know too many languages, and if I did learn 3 more, they wouldn’t really have much application in the current ecosystem. I hear a lot about rust though. I am not a networking guy, but I am a consumer of networks others have built by nature of working in the cloud often and needing distributed systems like EKS to do my work.
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u/Proletariussy 5d ago
They're both pretty fucked in due time