The Alt-Ac Job Beat Newsletter Post 3 2023-11-07

Hi Everyone,

I wanted to focus on healthcare jobs this newsletter.

In giving advice for searching the market, one way to orient your search is instead of looking for specific jobs, identify companies who do work you are interested in. Most people I imagine when you say tech jobs think FAANG jobs, but there are so many other companies who hire data oriented roles.

Healthcare is in my opinion a good fit for folks with a criminal justice background. At my day job I build machine learning models towards identifying fraud/waste/abuse in healthcare claims, as well as predict high risk in medical patients based on healthcare insurance claims. It is really very similar to the types of predictive models I built in my research with police departments.

Different types of healthcare companies that hire data roles are:

You can pretty much always go on CVS's website and apply for jobs. Or if you know of a large hospital system in your area, it is worth checking out if they have roles.


I added a ton of healthcare roles this past week. So check out the spreadsheet for them all

For a rundown of several of the roles:

I try to include an array of roles/salaries in the spreadsheet -- moreso so you can get a feel of the different types of jobs on the market and salary range expectations.


Jenn Reingle-Gonzalez, is Vice President of Population Health at Meadows Mental Health Institute (a Think Tank). Jenn's Phd is in epidemiology, but she has published a ton in criminal justice areas, so I would consider very similar background to many CJ Phds.

For more seasoned academics, you can be hired directly into Director (or even higher) level positions. But those are typically not "I applied to that position on LinkedIn", more likely you are recruited or have direct connections with the company.


For those looking to get an introduction to machine learning, my favorite resource is the StatQuest youtube library. Josh Starmer goes though simple examples of the math step by step. Here is the first in his series on boosted models for example.

I find those better intro material than any of the books I have read.

Best, Andy Wheeler