Mid‑career help: I’m in a long‑term research/analysis role, and the data scientists are lapping my pay?
Me: Mid‑career professional in a research/knowledge‑services role at a public institution. PhD (public policy). 20+ years in. Salary: $114k. I stayed because the schedule was good, the work was meaningful, and I got to be present for my kids’ lives. I don’t regret that trade‑off.
But the last two weeks have made me realize I may need to future‑proof myself.
- We aren’t backfilling a junior position; the remaining staff is expected to absorb the workload. When I started, our team was much larger. Now it’s down to two of us.
- My institution just posted a Data Scientist position with a $100k–$125k starting range.
Qualifications for the DS role:
- Bachelor’s degree in a quantitative field
- 5+ years of data‑analysis experience
- Applied statistics (regression, hypothesis testing, research design)
- NLP/LLM experience
- Python + R
- SQL
- Tableau/Power BI
- Ability to explain technical methods to non‑technical audiences
So someone with a bachelor’s degree (plus experience) is going to walk in and make almost what I make or more.
I’m late to the game, but I’m trying to catch up. This fall I enrolled in:
- Intro to Applied Data Science Techniques
- Machine Learning I
- Artificial Intelligence Awareness
I’m stumbling through Python (my background is BASIC from high school), and a lot of the coursework feels like Canvas discussion‑board busywork. I don’t feel like this is getting me where I need to be fast enough.
I’m not worried about losing my job tomorrow, but I’m 49, and I’m trying to figure out the last 20 years of my career. I see the writing on the wall, and I’m probably 2–3 years late to this party.
Any advice would be appreciated.