[yold__]

> Generally they make 25-50% more than a similar level vanilla software engineer.

It's often even less in my experience. Despite having a "unicorn" skillset (soft-skills, advanced degree, domain experience, and SWE experience), I make about as much as a vanilla SWE. There are a huge number of inexperienced PhDs that want into the field, and we are flooded with resumes every time a DS leaves. Also, most of the time, models don't really matter. What makes or breaks most DS projects is soft-skills, stakeholder management, and data cleaning / feature engineering.

[lytefm]

> Also, most of the time, models don't really matter. What makes or breaks most DS projects is soft-skills, stakeholder management, and data cleaning / feature engineering.

I have the same impression. I did my Master's degree in data science, but I quickly realized that coming up with ideas and running the models is the easy part. Doing the engineering work + synthesizing everything such that value creation occurs is more difficult.

I'm happily doing mostly data engineering + stakeholder management instead of hyperparameter tuning.

[apohn]

>I'm happily doing mostly data engineering + stakeholder management instead of hyperparameter tuning.

Agreed. I actually like that in DS you can have a job where you are involved in the end-to-end of a business problem and that you need to have a mix of skills (e.g. Act like a Product Manager and an Engineer) to succeed. And it's not just "Today I get to crank out yet another tile on the Kanban board."

[greatpostman]

By ml roles I was referencing research/deep learning type of jobs.

[lytefm]

Sure "Machine Learning Research at top tier AI company" is a different boat.

I'm talking more about "Data Science/ ML Department at a typical company". You won't see salaries above comparable SWE roles there. Most likely, the SWEs will be better off.