u/MathStat2019

I’m a tenure-track Assistant Professor in Data Science at a teaching-focused university, and I’m seriously rethinking the long-term sustainability of staying in academia.

The main issue is financial pressure. In my area, rent has increased ~60–80% since before the pandemic, while salaries in the College of Science have stayed mostly flat. I also notice a clear pay gap like Data Science roles in CS and Business schools are often paid significantly more than similar roles in Colleges of Science.

I have a PhD in Machine Learning and strong industry opportunities, where I could likely earn 2–3x my current salary. However, recent tech layoffs make me hesitant to leave the stability of a tenure-track position. On top of that, being at a teaching-focused university means a heavy teaching load and limited research resources, which adds to the concern about long-term career and financial growth.

So I feel stuck between:

Academia: stability but low pay growth
Industry: much higher pay but more uncertainty

Would appreciate perspectives from people who have made the switch (or chose not to). How did you decide?

I’m a tenure-track Assistant Professor in Data Science at a teaching-focused university, and I’m seriously rethinking the long-term sustainability of staying in academia. In my area, rent has increased ~60–80% since before the pandemic, while salaries in the College of Science have stayed mostly flat. I also notice a clear pay gap. For example, Data Science roles in CS and Business schools are often paid significantly more than similar roles in Colleges of Science.

Academia: stability but low pay growth Vs. Industry: much higher pay but more uncertainty

Would appreciate perspectives from people who have made the switch (or chose not to). How did you decide?

Is leaving a tenure-track job for industry a mistake?

Is leaving academia for industry worth it in ML/Data Science?