Also, best to clarify that this review is only about “working at a government agency that funds relevant research”, and that this is only one out of their 3 mentioned highly-effective careers related to grantmaking (at the bottom), and that the other two would need a different analysis.
I also think that if the intent is to advise on careers, you need to do some analysis of the team of E-ARPA. Variables that come to mind are: size of team, how many of each role, how senior each person seems (for thoughts on how soon a person can get hired in such a role, and maybe even, in the case of junior employees, where they could go from there career-capital-wise), and a rough guesstimate of how much each role contributed to the overall annual grantmaking decisions of E-ARPA.
Also a minor wording note.. You say: ”We chose ARPA-E because other ARPA agencies are explicitly called out by 80,000 Hours profile of grantmaking (i.e., DARPA, IARPA)”
“Called out” has negative connotations, so I’d probably say “mentioned”, “referred to”, or “brought up” instead. That terminology confused me—I thought you were saying you only chose ARPA-E because the others had been essentially ruled out. I was a bit aghast thinking you’d chosen an example in a category where others had already been shown to be moot or something , and that’s why I dug for and read the original 80K piece >.>
Phew, sorry that was so much seemingly-critical feedback, but to clarify I (not a researcher or data scientist) think what you did do is good and I’m happy you reviewed this career path, which tends to, I think, be unfortunately skipped in many career discussions. I strong upvoted the post.
Cool work! Props that you allow for people using their own discount rate, as your first footnote is a good point.
I think that for transparency and ease of reader understanding, you ought to link the 80K’s article on grantmaking for most-pressing problems. Similarly, linking info on Squiggle would be good.
Also, best to clarify that this review is only about “working at a government agency that funds relevant research”, and that this is only one out of their 3 mentioned highly-effective careers related to grantmaking (at the bottom), and that the other two would need a different analysis.
I also think that if the intent is to advise on careers, you need to do some analysis of the team of E-ARPA. Variables that come to mind are: size of team, how many of each role, how senior each person seems (for thoughts on how soon a person can get hired in such a role, and maybe even, in the case of junior employees, where they could go from there career-capital-wise), and a rough guesstimate of how much each role contributed to the overall annual grantmaking decisions of E-ARPA.
Also a minor wording note.. You say:
”We chose ARPA-E because other ARPA agencies are explicitly called out by 80,000 Hours profile of grantmaking (i.e., DARPA, IARPA)”
“Called out” has negative connotations, so I’d probably say “mentioned”, “referred to”, or “brought up” instead. That terminology confused me—I thought you were saying you only chose ARPA-E because the others had been essentially ruled out. I was a bit aghast thinking you’d chosen an example in a category where others had already been shown to be moot or something , and that’s why I dug for and read the original 80K piece >.>
Phew, sorry that was so much seemingly-critical feedback, but to clarify I (not a researcher or data scientist) think what you did do is good and I’m happy you reviewed this career path, which tends to, I think, be unfortunately skipped in many career discussions. I strong upvoted the post.