(Background: Have worked in trading since late 2013, with one ~18 month gap. Have also spoken to >5 people facing a decision similar to this one over the years. This is a set of points I often end up making. I'm moderately confident about each statement below but wouldn't be surprised if one of them is wrong.)

I think both of these paths are very 'spiky', in the sense that I think the top 10% has many times more impact (either via donations or direct work) than the median. From a pure altruistic perspective, I think you mostly want to maximise the chance of spiking. 

One of the best ways to maximise this is to be able to switch after you realise you aren't in that category; in trading I think you're likely to have a good sense of your appoximate path within 2-4 years, so in the likely even that you are not hitting the high end at that point you have an opportunity to switch, if your alternate allows you to switch (often but certainly not always the case). Similarly, I'd try to work out what flexibility you have on the AI PhD path; if you do in fact find the day-to-day frustrating and decide to quit in order to avoid burnout, what are your options? If you can switch either way, that's great and this largely ceases to be an important consideration.

On a related note, and echoing some others, 2-4 years undoubtedly sounds like a long time now but it's actually a pretty small fraction of your career. Don't feel like a 'bad' choice now will forever condemn you to an inferior path! Any choice that does actually lock you in this way is probably a bad choice for that reason alone, but again usually this feels like it is the case more than it is actually the case. 

Some people underestimate quant trading earnings at top-tier firms, because the firms are extremely cagey about them. FWIW, I think >$1m annual earnings within 5-10 years is more like the 40th-80th percentile case depending on firm, while the 'spike' case pushes into >$5m within their first decade.  That's for trading. Software engineer earnings at these firms I have a weaker sense of; they can either essentially match the traders or fall significantly behind (I don't currently know of a case where it runs ahead); this depends heavily on the specific firm.

Predicting what you're more likely to spike in advance is hard, and is going to be a question of personal fit, so difficult for us to answer, I just think that's the right question. That said, there are some things in your post that make me think AI is more likely to be your life's work:

• Writing code long-term (20+ years) sounds incredibly draining
• I know E2G is high impact but sometimes it doesn't feel that way; definitely feel like a sell out
  ....
• Intellectually interesting; kind of a dream career

Sometimes people feel things like the above and assume everyone else feels the same way. As someone who has heard both pro-E2G and pro-AI versions of all of these points, the one thing I'm confident of is that this is not the case. As a community, there are worse ways we could coordinate this than having all the people who are more excited on a gut level about working at quant firms do that, and all the people who are more excited about working on AI do that. I do think there are more of the latter than the former, but that's ok; one person E2G-ing at that level (especially if they spike) can fund many other people doing direct work. 

The above is all written from a 'For the Greater Good' perspective. It sounds like a lot of what is pulling you towards quant work is that it's the safe, already-available, almost-certainly-going-to-work-out-well-for-you-personally option. This is a reasonable thing to pay attention to! Just how much attention depends on things like your general level of financial security, do you have or expect to have dependents or other major family committments, how wide/deep is your career path if a particular opportunity goes away, what kinds of backup (e.g. parents you could move in with) do you have, etc. Try not to assume things will work out ok, but equally try not to assume one bad call will end it all if you have layers of protection. This is incredibly variable by individual, and most EA advice is calibrated for young people who are pretty secure, don't have large external obligations, and have solid backup. This in turn strongly points to taking a higher-than-usual level of risk in your altruistically-motivated endeavours. If that's you, then great. If not, it might be worth some reflection about to what extent you can afford to, e.g. aim for the PhD and fail. 

Hey Anon,

I was in a similar situation to this with job offers from MIRI (research assistant) and a top quant trading firm (trading intern, with likely transition to full-time), four years ago.

I ended up taking the RA job, and not the internship. A few years later, I'm now a researcher at FHI, concurrently studying a stats PhD at Oxford.

I'm happy with what I decided, and I'd generally recommend people do the same, basically because I think there are enough multi-millionaire EAs to place talent at a large premium, relative to donations. Relative to you, I had a better background for trading, relative to academic AI - I played Poker and gambled successfully on political markets, but my education was in medicine and bioinformatics. So I think for someone like you, the case for a PhD would be stronger than for me.

That said, I do think it depends a lot on personal factors - how deeply interested in AI (safety) are you? How highly-ranked exactly are the quant firm, and the PhD where you end up getting an offer? And so on...

I'd be happy to provide more detailed public or private comments.

Congratulations on the quant trading firm offer! It sounds like right now you’re in a great overall position, and that you’re thinking things through really sensibly. A few thoughts: 

For examples of data drive policy roles, I wonder if you’d be interested in the type of research that the Center for Security and Emerging Technology does? 

With regard to earning to give, I’m sorry to hear that it doesn’t feel high impact. Do you think that might be better once you have money to donate, and are spending time carefully thinking through where that could do the most good? Or perhaps if you spent quite a bit of time chatting to other people earning to give, and so had more of the sense of being in a community doing that? If you haven’t yet, I wonder if it’s worth your chatting to some other people who have been earning to give for a while about how they’ve found it. Likewise talking to someone who has been a software engineer for a longish while about how they’ve found it over time sounds like it could be useful. 

On going into AI, I don’t know that I’d be worried about having negative effects if you don’t work in AI safety, because I’d expect if you didn’t go into AI safety there would be other roles in things like medical tech AI which would useful rather than neutral in expectation. On the other hand, it does sound kind of worrying to me for this path that you like the idea of research but don’t sound keen on the day-to-day. I think everyone finds research frustrating some of the time, so that seems totally fine, but I think if your overall sense is that you wouldn’t enjoy doing the research needed for a PhD, probably that wouldn’t be a great path for you. 

I’m guessing it’s pretty hard to turn down the quant firm offer, given that it’s a great job. If you decide you’re actually keen to see how you can do with publishing more in AI, I wonder if it’s worth asking them about pushing the offer for a while? They might be fine with you spending a few months or more publishing before coming to them. 

I imagine that right now this is feeling like a stark crossroads, where you have to go one direction or the other for life. That doesn’t sound right to me - I know various people who have worked at a hedge fund for a few years and then gone into AI safety. Likewise if you do an AI PhD and decide against research, you’ll be in a great position to earn to give afterwards. So to the extent you can think of this decision as just one step forward, and as a further test of what you might like to do over the longer term, I think that sounds like a more accurate framing and one which will take the pressure off. It seems useful to remember that you’re in a great position, even if things are a bit intimidating right now!

You should take the quant role imo. Optionality is valuable (though not infinitely so). Quant trading gives you vastly more optionality. If trading goes well but you leave the field after five years you will have still gained a large amount of experience and donated/saved a large amount of capital. It's not unrealistic to try for 500K donated and 500K+ saved in that timeframe, especially since firms think you are unusually talented. If you have five hundred thousand dollars, or more, saved you are no longer very constrained by finances. Five hundred thousand dollars is enough to stochastically save over a hundred lives. There are several high impact EA orgs with a budget of around a million dollars a year (Rethink Priorities comes to mind). If trading goes very well you could personally fund such an org. 

How are you going to feel if you decide to do the PHD and after five years you decide that it was not the best path?  You will have left approximately a million dollars and a huge amount of earning potential on the table. You could have been free to work for no compensation if you want. You would have been able to bankroll a medium sized project if you keep trading. 

There are a lot of ways to massively regret turning down the quant job. It is plausible that the situation is so dire that you need to drop other paths and work on AI safety right now.  But you need to be confident in a  very detailed world model to justify giving up so much optionality. There are a lot of theories on how to do the most good. Stay upstream. 

Consider tech roles in government! Governments do a lot of high-impact work, especially in the areas that most EAs care about (global health and development, long-term risks), so working in government could allow you to work directly on these areas and build connections that may open the doors to higher-impact work. If you're a U.S. citizen, you can apply for the Civic Digital Fellowship (for students) or the Presidential Innovation Fellowship (for more seasoned technologists), both of which place technologists in the federal government.

Hello! I am a math BS, CS MS w/ 8 years experience, am in Fintech doing AI and deep learning (not as a quant, but close), so hopefully I can shed some light for you :) To cut to the chase, I'd strongly consider the quant trading firm option, largely just because you have a great offer and shouldn't overlook that. (especially if you think the work-life balance will be good! That is a major downside to many trading jobs)

First, you can get 1000 opinions about a phD, but my personal opinion is to skip it. It does help lend some credibility, but sacrificing 5 years of career progression and salary is just such a high cost. I work with a lot of PhDs and I hold my own just fine.  

Second, I've been donating 10% of my income for about 5 years now, and it ABSOLUTELY DOES feel good. Especially if you are like me and like looking at numbers and can let go of not "seeing" the impact first hand. I have a family member who did peace corp, and I feel just as strong connection to  my impact as they do. I had the same hesitations you did, but I ultimately realized my desire to "feel" like I was doing good was more tied to a desire to "show off" on linked in that I was doing good based on my employer or title. Most friends and family don't know I E2G, and I'm fine with that. I'm still doing a hell of a lot of good, and I sleep fine at night. 

Third (not about PhD, but regarding quant vs policy), ask yourself: if you pick wrong, which switch will be easier. Few trade shops will hire someone with a non-technical policy background, even in AI. Many AI policy jobs would love to hire a highly technical person who has inside knowledge on how the financial industry works. 

Finally, don't underestimate the intellectual stimulation of a quant job. To an outsider, I stare at a stock market activity and python code all day. But I find it incredibly thought provoking. Our company has "journal clubs" and I find time to read ML articles and books. Obviously if you truly hate coding, then avoid it. But I still code daily, and it's not nearly as "draining" as I expected. Don't forget AI is hot stuff in fintech right now, so the two topics are not mutually exclusive.

Good luck!!

Working at a ritzy quant firm shouldn't impact your competitiveness for PhD programs too much (could even improve it), and if you're getting $1M+ / 5y E2G-worthy offers halfway through ugrad (and have already published!), you'll probably still be able to get comparable offers if you decide to e.g. master out. So in that regard, it probably doesn't matter too much which path you take, since neither preclude reinvention.

If it were me, I'd take the bird in hand and work in the quant role... but if I felt myself able to make more meaningful "direct" contributions, focus on not just E2G'ing but also achieving financial independence as soon as possible. PhD program stipends are quite a bit lower than industry pay (at my current school, CS students only make around ~$45k / y), so being able to supplement that income with proceeds from investments would free you from monetary concerns and let you focus your attentions on more valuable pursuits (e.g. you wouldn't have to waste time on unpleasant trivialities, like household chores, if you could instead hire a regular cleaning service + meal delivery. Hell, spend another year or two at the firm and get yourself a part-time personal assistant for the duration of the grad program to manage your emails for you haha). Focus on solving those claims on your time that can be most cheaply solved first, to give yourself greater opportunities to direct more valuable hours down the line.

Regarding the data-driven policy path, my sense is that unfortunately, most policy work in the U.S. today is not that data-driven, though there's no doubt that that's in part attributable to human capital constraints. Two exceptions do come to mind, though:

1. Macroeconomic stabilization policy (which is one of Open Philanthropy's priority areas) definitely fits the bill. Much of the work on this in the U.S. occurs in the research and statistics and forecasting groups of various branches of the Federal Reserve System (especially New York, the Board of Governors in D.C., Boston, Chicago, and San Francisco). These groups employ mathematical tools like DSGE and HANK models to predict the effects of various (mainly but not exclusively monetary) policy regimes on the macroeconomy. Staff economists working on this modeling regularly produce research that makes it onto the desks of members of the Federal Open Markets Committee and even gets cited in Committee meetings (where U.S. monetary policy is determined). To succeed on this path in the long-term you would need to get a PhD in economics, which probably has many of the same downsides as a PhD in computer science/AI, but the path might have other advantages, depending on your personal interests, skills, values, motivations, etc. One thing I would note is that it is probably easier to get into econ PhD programs with a math-CS bachelor’s than you would think (though still very competitive, etc.). The top U.S. economics programs expect an extensive background in pure math (real analysis, abstract algebra, etc.), which is more common among people who studied math in undergrad than among people who studied economics alone. A good friend of mine actually just started her PhD in economics at MIT after getting her bachelor’s in math and computer science and doing two years of research at the Fed. This is not a particularly unusual path. If you're interested and have any questions about it, feel free to dm me.
2. At least until the gutting of the CDC under our current presidential administration, it employed research teams full of specialists in the epidemiology of infectious disease who make use of fairly sophisticated mathematical models in their work. I would consider this work to be highly quantitative/data-driven, and it's obviously pertinent to the mitigation of biorisks. To do it long-term, you would need a PhD in epidemiology (ideally) or a related field (biostatistics, computational biology, health data science, public health, etc.). These programs are also definitely easier to get into with your background than you would expect. They need people with strong technical skills, and no one leaves undergrad with a bachelor's in epidemiology. You would probably have to get some relevant domain experience before applying to an epi PhD program, though, likely either by working on the research staff at someplace like the Harvard Center for Communicable Disease Dynamics or by getting an MS in epidemiology first (you would have no trouble gaining admission to one of those programs with your background). One big advantage of epidemiology relative to macroeconomics and AI is that (my sense is) it's a much less competitive field (or at least it certainly was pre-pandemic), which probably has lots of benefits in terms of odds of success, risk of burnout, etc. Once again, feel free to dm me if this sounds interesting to you and you have any questions; I know people who have gone this route, as well.

It's great that you have two very strong options! The answer probably comes down to your judgment on a few questions: a) What's the likelihood of a catastrophic AI accident in your lifetime? b) What's the likelihood your work could help prevent that? c) Where would you donate if you earn to give?

(I'm tempted to try to convince you to earn to give, because the opportunity you describe sounds excellent for you and for the world, and I'm pretty sceptical about AI research and excited about bednets! But ultimately you'll need to figure out your views on these things.)

First of all, you have shown an impressive amount of stamina! Well done.

My guess is that if you want to pursue this path, you should focus on getting more political contacts, for example get involved in party politics. I know a lot of people who worked for MPs (albeit in a different country) who got these roles via party political work.

First of all I want to echo Denise and Louis - great work on putting in so many applications, that must have been really tough! 

I think unfortunately there’s no clear rule of thumb for when to let go of your plan A, it depends a lot on your individual situation. For example people are very different in how unhappy the process of applying makes them, and also in how big a difference they feel there is between their plan A and their plan B. It does sound like you have quite a bit of evidence that it's going to be really hard to get to work for an MP in the near term, and also that the process of trying is taking its toll on you, which makes me think it could be worth starting to think a bit more about your other options and whether there are any of those you feel good enough about to start applying to.

I think you needn’t think about working on your plan B as necessarily precluding your plan A. You could, for example, take a pause on applying for jobs with MPS jobs and focus on getting a different role that you’d be happy doing long term, with the plan of once you’re settled in that doing some more skill building and doing another round of applying to work with MPs. Or you might apply for just a couple of the politics roles you think you’re most likely to get, and alongside that apply to other types of roles. 

You haven’t said anything about other options you’re considering. I wonder if there are other career paths that actually might be pretty appealing to you? For example if you were working in the civil service you'd still be an important part of the political process. 

If you haven’t yet, you might consider asking some of the people who turned you down for feedback on why you didn’t get further in the process. It’s not always easy for people to provide, but it seems like it would be really useful for you to know if you should actually take the lack of offers as evidence that it isn’t as good a match for your skills as you thought, or if there’s simply one particular area you need to work on, or just that you were unlucky. 

I'd agree with what Michelle says, though I also wanted to add some quick thoughts about:

What's a good rule of thumb for letting go of your Plan A?

One simple way to think about it is that ultimately you have a list of options, and your job is to find and pick the best one.

Your Plan A is your current best guess option. You should change it once you find an option that's better.

So, then the question becomes: have you gained new information that's sufficient to change your ranking of options? Or have you found a new option that's better than your current best guess?

That can be a difficult question. It's pretty common to make a lot of applications in an area like this and not get anywhere, so it might only be a small negative update about your long-term chances (especially if you consider Denise's comment below). So it could be reasonable to continue, though perhaps changing your approach – we'd normally encourage people to pursue more than one form of next step (i.e. apply to a wider range of common next steps in political careers, and then see which approach is working best).

Another good exercise could be to draw up a list of alternative longer-term paths, and see if any seem better (in terms of potential long-term impact, career capital, personal fit and satisfaction).

It's great that you've been so persistent! It seems like you're fairly set on politics - what is it that motivates you to work on that, and are there any other routes to do something similar?

This is a fantastic career plan! And thank you very much for your article on being an expert in hardware, that seemed like a really useful synthesis, and I imagine will be really valuable for others considering working in this area.

I don't have much to add because it seems like you're thinking all this through really carefully and have done a lot of research. A few thoughts:  

• Application processes seem to me to have a lot of noise in them. So I wouldn't take a single rejection from AAAS as much evidence at all about you not being suited for policy.
• There are a range of other policy options you might consider for testing this route, such as the Mirzayan Fellowship, which has the benefit of being just 12 weeks. Lots more eg Tech Congress and PMF described in this document. 
• My impression is that it's easier to move from more to less technical roles than the reverse, which may point in favour of working for a year or two in industry before doing years in policy (although as a counter to that, some things like PMF are only an option up to ~2 years out of your degree)
• AI Impacts might be another organisation to have on your radar for maybe doing a short project with to test non-technical work. 

I think it depends a lot on industry. In the world of startups frequently changing jobs doesn't seem that unusual at all. In finance, on the other hand, I would be very suspicious of someone who moved from one hedge fund to another every two years.

It also depends a bit on the role. A recent graduate who joins an investment bank as an analyst is basically expected to leave after two years; but if a Director leaves after two years that is a sign that something was wrong. Working as a teacher for two years and then quitting looks bad, unless it was Teach for America, in which case it is perfectly normal.

Hi Matt,

This is a common concern, though I think it's helpful to zoom out a bit – what employers most care about is that you can prove to them that you can solve the problems they want solved.

Insofar as that relates to your past experience (which is only one factor among many they'll look at), my impression^[1] is that what matters is whether you can tell a good story about (i) how your past experience is relevant to their job and (ii) what steps have let you to wanting to work for them.

This is partly an exercise in communication. If your CV doesn't naturally lead to the job, you might want to spend more time talking with friends / advisors about how to connect your past experience to what they're looking for.

It depends even more on whether you had good reasons for changing, and whether you've built relevant career capital despite it.

I can't evaluate the latter from here, so I might throw the question back to you: do you think you've changed too often, or was each decision good?

I'm sympathetic to the idea that early career, a rule of thumb for exploration like "win, stick; lose, shift" makes sense (i.e. if a career path is going ahead of expectations, stick with it; and otherwise shift), and that can lead to lots of shifting early on if you get unlucky. However, you also need to balance that with staying long enough to learn skills and get achievements, which increase your career capital.

I’m sorry, that sounds like a really frustrating position to be in. From my standpoint, getting to financial independence itself sounds impressive and worth it, rather than a waste. But I see why it wouldn’t feel that way given how hard you need to work on the skills. While I really like ‘So Good They Can’t Ignore You’, I do wonder if it’s setting this crazy high target to say the work you do should be work you’d do whether you got paid or not. It feels like the ‘meaning’ we get out of work will often need to be a bit broader than that – for example being what Jack mentioned that the purpose is coming from being able to donate more than you would otherwise and thereby help others. I wonder if you might enjoy this person's take on how to find meaning in work?

I think what I’d take from what you’ve said and the above is that the other things you’ve been trying out sound pretty good, and that it could be good to think more about whether you could be happier doing any of them (for example, you mention data science as something that would be useful outside a corporate setting), and if so, going further into learning about or trying them. (By the way, on data science you might enjoy this podcast of ours.)

Personally, I found the Happiness Journal and the book Designing Your Life pretty useful for getting a better sense of my North Star, though you might not like that kind of thing!

^This. I have been battling with the exact same issue for the past few years. Thank you for putting the feelings into words so remarkably. Eagerly following this thread to see what other members have to share. 

Sorry to hear about your struggles.

I'm actually strongly considering pursuing an earning-to-give route. I don't expect to be in love with an ETG job, but I do expect to derive significant purpose and meaning from it because I would be doing a lot of good by donating more money. I would also plan to have at least a little bit more money to personally spend (although who knows maybe I won't feel I need it). 

If I pursue ETG I plan to put quite a bit of personal effort into determining where I should donate, which I expect to be quite an interesting, intellectually-stimulating and rewarding exercise.  I also plan to share these thoughts with the EA community. I think I would identify as an 'ETG-er' and may even try to make a name for myself as someone who can advise others on where to give (I'm uncertain how well that might work out though).

Do you think that you may be able to pursue ETG and derive the meaning and purpose that I hope to? One really can do a tremendous amount of good through donating money and it sounds like you have good potential to do so.

I think a lot of the day-to-day feelings of fulfillment in high-impact jobs come from either: 1) being part of a workplace community of people who really believe in the value of the work, or 2) seeing first-hand the way in which your work directly helped someone. I don't really think the feelings of fulfillment typically come from the particular functional category of your role or the set of tasks that you perform during the workday, so I wonder how informative your experiments with data science, for instance, would be with respect to the question of identifying the thing that you feel you "must do," as you put it. If I had to guess, I'd speculate that the feeling you're looking for will be more specific to a particular organization or organizational mission than to the role you'd be filling for organizations generally.

I think lots of people can relate to this sentiment! 

I could recommend having a look at Escape the City which provides a list of career opportunities for mid-career professionals wanting more social impact in their work: https://www.escapethecity.org/

If you are interested in short or long term volunteering with your tech skills, I can recommend a number of organisations that provide ample opportunities for this in the UK:

https://techforuk.com/
"Tech For UK aims to enable people to transform British democracy through technology and digital media that impacts the systems not just the symptoms of its problems."

https://democracyclub.org.uk/
"We build digital tools to support everyone’s participation in UK democracy. Our services are trusted by organisations in government, charities and the media, and have reached millions of people since 2015."

http://md4sg.com/
"Mechanism Design for Social Good (MD4SG) is a multi-institutional initiative using techniques from algorithms, optimization, and mechanism design, along with insights from other disciplines, to improve access to opportunity for historically underserved and disadvantaged communities. Members of MD4SG include researchers from computer science, economics, operations research, public policy, sociology, humanistic studies, and other disciplines as well as domain experts working in non-profit organizations, municipalities, and companies."

Out of curiosity, how long did you do your experiments in UX / Data Science / etc. for?   Maybe it would pay to try spending more time in these functions?   You could transition to data science and work for a year and half, then work for a year in UX for example (maybe do a bootcamp as a refresher / to build career capital).  Of course this is easier said than done - but I feel like it might take a long time before you can really assess how much a role aligns with your strengths, as it might take many months just to onboard to the role.   

I'm in my 20s working as a software engineer for a large US tech company and I hope to transition to some other roles for a few years if possible before committing to one role.  

Also, maybe it would be worth transitioning to a different company or team where you can feel that you work is having a greater impact on customers / on the world?   I feel like it can be a bit hard to feel your impact as a software engineer because usually you are usually not client facing.   But I imagine that your work might feel more impactful at a mission driven startup or if you are working as sales engineer and get to work with clients face to face periodically.  

This might be too elementary for you, but in college I benefited from Model Thinking by Scott Page. It's a breezy introduction to a long list of popular models used in the social and empirical sciences, and I think plausibly had a small effect on my general perspective of trying to see the world in terms of many simple models (vs eg "model-free" intuitions, or a single grand overarching model).  

Hi Jia,

There's a lot of options! Could you clarify which problem areas do you want to work on, and which longer-term career paths are you most interested in?

Hey Jeremy! Myself and Joan Gass at CEA, and Markus Anderljung at FHI,  all use skills like the ones you mention above, from our consulting backgrounds, at non-profits. 

I sometimes look at this filter on the 80K job board and one example of a role you might like is this one. I also think that working in government is often a good thing to do, and so maybe there could be some US trade/aid organisations which you might find interesting, and also this talk. If you think that consulting means you can boost the productivity of companies and lead to economic growth overall, then that could be interesting.

Hi Jeremy,

Glad to hear things have gone well!

I'd say it's pretty common for people to switch from management consulting into work at EA orgs. Some recent examples: we recently hired Habiba Islam; GPI hired Sven Herrmann and Will Jefferson; and Joan Gas who became the Managing Director of CEA a year ago.

As you can see, the most common route is normally to work in management or operations, but it doesn't need to be restricted to that.

If you want to pursue the EA orgs path, then as well as applying to jobs on the job board, follow our standard advice here (e.g. meet people, get more involved in the community).

Just bear in mind that there aren't many positions per year, so even if you're a good fit, it might take some time to find something.

For this reason, it's probably best to pursue a couple of other good longer-term paths at the same time. Another common option for someone with your background would to do something in policy, or you could try to work in development.

With this strand in particular:

helping others think about their own giving and the financial side of maximizing donations / minimizing taxes

There is a need for this, and there's a bit of a philanthropy advisory community building up in London around Founder's Pledge, Veddis and Longview Philanthropy. I'm not sure there's yet something like that in the States you could get involved in. You might be able to start your own thing, especially after working elsewhere in EA or philanthropy for 1-2 years. (Example plan: work at a foundation in SF -> meet rich tech people -> start freelance consulting for them / maybe joining up with another community member.)

Either way, I'd definitely encourage you to think hard about which impactful longer-term paths might be most promising, and what those would imply about the best next steps. You already have a lot of general career capital, and big corporate middle management experience is not that relevant to working at smaller non-profits, so I doubt continuing in the corporate sector will be the optimal one, unless you find something really outstanding.

Hi Will,

James is asking a good question below, but I'm going to dive into a hot take :)

If you're about to start university, I'm wondering if you might be narrowing down too early. My normal advice for someone entering college for figuring out their career would be something like:

1. Draw up a long list of potential longer-term options.
2. See if you can 'try out' all of these paths while there, and right after.

You can consider all the following ways to try out potential paths, which also give you useful career capital:

1. Doing 1-2 internships.
2. Doing a research project as part of your studies or during the summer.
3. Going to lots of talks from people in different areas.
4. Getting involved in relevant student societies (e.g. student newspaper for the media)
5. Doing side projects & self-study in free time (e.g. building a website, learning to program)
6. Near the end, you can apply to jobs in several categories as well as graduate school, and see where you get the best offers.
7. And even after college, you can probably then try something and switch again if it's not working.

So, going in, you don't need to have very definite plans. Besides being able to explore several paths within earning to give, I'd also encourage you to consider exploring some outside. As a starting point, some broad categories we often cover are: government and policy options, working at social impact organisations in your top cause areas (not just EA orgs), and graduate study (potentially leading into working at research organisations or as a researcher). Try to generate at least a couple of ideas within each of these.

Which subject should you study? A big factor should be personal fit – one factor there would be whether you'll be able to get good grades in moderate time (since you can use that time to do the steps above and also to socialise - and many meet their lifetime friends and partner at university). Besides that, you could consider which subject will (i) be most helpful to the longer-term options you're interested in and (ii) most keep your options open. If in doubt, applied quantitative subjects (e.g. economics and statistics) often do well on this analysis.

There's a bunch more rough thoughts here.

You seem to assume that if (and only if) you do well in a good college, then you will almost certainly be good at direct work. I'm not convinced that there necessarily is that much of a correlation because these things are so very different. I myself did quite badly in a mediocre university but people seem to think that I have been doing well working as a researcher at an EA organization.

Hey Will! Would you be able to say anything more about why you didn't like the 2 years of college that you did? What sort of college degrees are you looking into right now? :)

I think this is a really hard question, and the right answer to it likely depends to a very significant degree on precisely what you’re likely to want to do professionally in the near and medium-term. I recently graduated from a top U.S. university, and my sense is that the two most significant benefits I reaped from where I went to school were:

1. Having that name brand on my resume definitely opened doors for me when applying for jobs during my senior year. I’m actually fairly confident that I would not have gotten my first job out of college had I gone to a less prestigious school, though I think this only really applies to positions at a fairly narrow set of financial services firms and consulting firms, as well as in certain corners of academic research.
2. I think I personally benefited from a significant peer effect. My specific social circle pushed me to challenge myself academically more than I likely otherwise would have (in ways that probably hurt my GPA but served me well all things considered). That said, I know that the academic research on peer effects in education is mixed to say the least, so I’d be hesitant to extrapolate much from my own experience.

I’m not sure how to weigh the importance of the first of those considerations. On the one hand, your first job is just that: your first job. It doesn’t necessarily mean anything about where you’ll end up at age 35. On the other hand, I do feel like I have observed this phenomenon of smart people graduating from relatively unknown universities and really struggling to find interesting work during their first several years out of college and then eventually resigning themselves to getting a master’s degree from a more well-known school (sometimes in a field where the educational benefit of the degree is relatively low) just so that they can get in the door to interview for jobs in their field of choice. This obviously comes at a significant cost, both in terms of time and—often but not always—in terms of money. That said, in some fields, you just do need a master’s to get in the door for a lot of roles, no matter where you went to undergrad or what you did while you were there, and maybe that’s all that’s really behind this.

Another thing potentially worth noting is that, in my experience, it seems as if U.S. research universities are most usefully divisible into three categories with respect to their undergraduate job placement: universities that “high-prestige” employers are unlikely to have heard of, universities that “high-prestige” employers are likely to have heard of and have vaguely positive associations with, and finally, the set of Harvard, Princeton, Yale, MIT, and Stanford (these are distinguished not only by their name brands but also by the extent of their funding and support for undergraduate research and internships, the robustness of their undergraduate advising, and other more “experiential” factors). There are certainly exceptions to this breakdown (the financial services and consulting firms mentioned above definitely differentiate between Penn and Michigan), but by and large, my sense has been that controlling for “ability,” the difference in early-career outcomes between a Harvard graduate and a Penn graduate is significantly larger than the difference in early-career outcomes between a Penn graduate and a Michigan graduate (note: the specific schools chosen as examples within each cohort here are completely arbitrary). Accordingly, I don’t think that very many people generally have a strong professional reason to transfer from UCLA to Brown or from the University of Virginia to Dartmouth, etc. However, I buy that those at lesser-known schools may, in many circumstances, have a strong professional reason to transfer to their flagship state school.

Other good reasons to transfer, I think, include transferring for the purpose of getting to a particular city where you know you want to work when you graduate, with an eye toward spending a portion of the remainder of your time in college networking or interning in your field of choice. In particular, I think that if you want to work in U.S. (national) policy after graduation, transferring to a school in the Washington, DC Metropolitan Area can be hugely beneficial. The same goes for financial services in the New York City Metropolitan Area, entertainment in Los Angeles, and (perhaps, though I am less sure about this) tech in the San Francisco Bay Area. In your case, it might be worthwhile to submit a transfer application to Georgetown with the aim of trying to forge some connections at the Center for Security and Emerging Technology (or perhaps the Center for Global Health Science and Security if you are interested in biosecurity policy), both of which are housed there. One other very strong reason to transfer, it seems to me, would be if you wanted to work on AI, but your current school didn’t have a computer science department, like a local state school near where I grew up. I assume from your post that that isn’t your situation, though.

Finally, I wouldn’t underestimate the importance of mental health considerations, to the extent that those may be at all relevant to your choice. Mental health during college can have a huge impact on GPA, and while where you go to undergrad will only really be a factor in determining your grad school prospects for a relatively narrow set of programs (mainly, I think, via the way it affects the kinds of research jobs you can get during and post-college), GPA is a huge determinant of grad school admissions across basically every field, so that is important to bear in mind. The transfer experience, from what I have heard, is not always easy, especially, I imagine, in academic environments that are already very high-pressure.

If you’d like to talk through this at greater length, feel free to DM me. To the extent that my perspective might be useful, I’d be more than happy to offer it, and if you’d just like someone to bounce ideas off of, I’d be happy to fill that role, as well.

Also have you seen this? 

Hi Jack! I worked in consulting at EY for four years before joining CEA in operations, and you might find a role in management/leadership/operations interesting. You might find a direct role that's more fun than ETG (I think I did!)

I don't really know anything about the best ETG routes, but one that strikes me that could be big business at the moment is insolvency and restructuring - lots of organisations will be unfortunately going through that so there could be quite  a few roles. 

Also a few friends of mine who were at PwC worked in deals/valuations and then left to get high-paying jobs doing (I think) the same thing at smaller  places where the partners took less of the margin. Maybe that could be an option.

That sounds like a  huge range of options. With an MPP-MBA you might do well in policy. Are there any government or related roles you think you'd be interested in? And is there a particular area you'd like to work in? E.g. if you were more passionate about animal welfare than nuclear security, that would suggest some pretty different career routes. 

If you DM me, I'd be happy to set up a quick Google Hangout to discuss a few internship options!

To Louis's point, if you're interested in climate or animal welfare issues, I think joining an alternative protein startup — Nature's Fynd, or others — in a pre-MBA  intern role or post-MBA full-time role would be a great step. Even if you aren't planning to ETG via a non-EA career, there's a good chance you'd earn attractive compensation between salary and a (potential) exit that could make high-impact but perhaps less financially stable subsequent EA career paths viable for you.

Knowing many PMF alumni who went on to high-impact policy roles, the PMF is also a great option for MPP and/or MBA students looking to begin policy careers.

I think staying where you are seems like a good option. There seems to be an assumption that just because you stay in the same job for the next few years you'll automatically be there for the next 15 - is that really true? Also maybe you could make a public commitment to leave after X years, or donate your income above a certain level to avoid getting lured in by the money side of it. 

Hi there, I would recommend talking to people who have done both paths and who share your higher-level goals and values.

If you haven't already, check out https://www.legalpriorities.org/ - maybe someone there would be worth talking to.

There is also an ex-barrister career advising at 80K, Habiba Islam.

Finally, I'm happy to tell you about what the lawyers do at my department in the civil service. If you're interested, DM me. 

What sticks out to me is that you're good at your job and you really enjoy it.  Under those circumstances, I see no need to change.  However, you do mention wasting 15 years of your life, if you enjoy it, I don't understand this line.

In terms of impact, is this driven by comparison to someone you know?  Does it seem like you're creating a problem unless this has been organically eating you up for a bit?  With that said, is it possible through networking you could get access to the board level roles/work, now?  If it's just for this endgame, it seems prudent to test this as early as possible.

Your musings on AI ethicist strike me as navel-gazing, you could be right or wrong, the only way to know is to trial some of these options to hopefully learn more.

(I'm a trader at a NY-based quant firm, and work on education and training for new traders, among other things.)

I'm nearly certain that your hiring manager (or anyone involved in hiring you) would be happy to receive literally this question from you, and would have advice specifically tailored to the firm you're joining.

The firm has very a strong interest in your success (likely more so than anyone you've interacted with in college), and they've already already committed to spending substantial resources to helping you prepare for a successful career as a trader. Answering questions like this one (even before you've "officially" started) is literally (part of) someone's job.

(I'm declining to answer the actual question not to be unfriendly, but because I think the folks at your future employer will have more accurate answers than I can give.)

Really glad to hear it seems useful!

Hey, great that you're thinking about this at this stage.

I hope that people with more experience in e.g. AI risk work will chime in, but here are a few quick thoughts from someone who did a bachelor's and master's in maths, has done research related to existential risk, and now does project management for an organization doing such research.

• I think either of maths, physics, or computer science can in principle be very solid degree choices. I could easily see it being the case that the decisive factor for you could be which you feel most interested in right now, or which universities you can get into for these different disciplines.
• Picking up the last point, I think the choice of university could easily be more important than the choice of subject. You say you want to stay near Zurich, but perhaps there are different universities you could reach from there (e.g. I think Zurich itself has at least two?). On the other hand, don't sweat it. I think that especially in quantitative subjects and at the undergraduate level, university prestige is less important, and at least in the German-speaking area there aren't actually huge differences in the quality of education that are correlated with university prestige.
  • However, this will still be a significant factor, especially in some careers.
• Similarly, what you do within your degree can easily be more important than its subject. I.e. which courses do you take, which topic do you write your thesis in, etc. In particular, if you're interested in AI risk, there is a lot of advice available on what to prioritize within your degree (see e.g. here + links therein).
• Finally, what you do outside of your degree can easily be more important than its subject. For example, deep learning - an area highly relevant to AI risk - has very low barriers to entry compared to most areas of maths or physics. It could be good to find out early if you're interested in and good at machine learning, for instance by taking online courses such as this one or working through OpenAI's "Spinning Up" materials. This stuff really doesn't require much prior knowledge; it could be accessible to you even know, or else after the first 1-2 years of study.
• I don't think that research on AI risk requires a degree in computer science. There are many mathematicians and physicists doing technical AI safety research, and more broadly for reducing AI risk we'll need social scientists, law scholars, policy advisors, and generally a multitude of people with a variety of expertise.
  • Yes, much (though not all) research on technical AI safety involves machine learning. For this, you'll need programming and software engineering skills, and you learn those in a computer science degree. However, you can also learn them in other degrees, or even fairly easily pick them up on the side. In addition, even the programming aspect of machine learning is overall importantly different from traditional programming.
  • On the other hand, for basically all technical AI safety research you'll need maths. You may be able to learn this better in a maths or physics than a CS degree; generally it's easier to move from a more abstract and theoretical background to more applied work than the other way around, so maths may leave most options open.
  • Yes, in maths or physics you'll learn many things that aren't very relevant to the AI risk work you may end up doing, but that's true for computer science as well. E.g. there are probably at most a few niches for how to apply courses on computability theory or databases (both typical CS subjects) to AI. On the other hand, I struggled to think of areas of physics that are clearly totally irrelevant to all AI risk work!
• Some of the above points apply less if you can access undergraduate degrees that focus specifically on e.g. machine learning. But even then, note that it's very possible to move later from maths or physics to machine learning, but harder the other way around.
• I've talked a lot about AI risk because you mentioned it, but I wouldn't narrow down on AI risk too quickly. Quantitative degrees leave open a lot of options including, for instance, global priorities research or some of the less explored paths mentioned here and here. Examples of mathematicians who've later done great EA-relevant work that's neither in academic mathematics nor AI risk include Owen Cotton-Barratt and David Roodman.
• Talking to students doing the degrees you're considering at the universities you're considering can be a good source of information about how the degree is actually like and similar things.

which path sounds the most interesting to you right now?  From what you've written, the impression I get is that you want to do mathematics.  Sounds like you're plenty smart and will succeed in whatever you put your mind to!

Hey Nick! 

a) 31 still seems pretty early in your career to me - presumably you expect to work 30 or 40 more years. So making sure you’re in a role you feel happy in sounds worth it even if it means some transition costs. I’d also expect you to have built up skills which are transferable to policy and even research: To do impactful research it seems important to keep in mind who will actually end up using the research and how. So transitioning at this point sounds fine to me. Having said that, working in marketing/outreach at impactful organisations also sounds like a great option if you feel good about it. 

b) Doing a degree seems fairly expensive in both time and money, so I could imagine it being better to try to do some work in the field before committing to a degree. That way you can find out whether you actually do enjoy working in the area, and what direction you might want to go in (hence what degree would make most sense for you). Either sound like reasonable options though. There are a few more considerations about when to do grad school in this article. 

On a) I think it depends on how well suited you are to the role and on b) Have you tried applying for roles in emerging technologies or security? This could be a cheap test to see if you might like working there, and whether you'd actually need to do further study.

Hi Nick,

I am also a marketing strategist, in Sydney and have spent a bit of time thinking about how to make my career more ‘effective’ (I had 80k coaching, Effective Animal Advocacy coaching, plenty more 1:1 chats/brainstorms). Anyway,  I’m happy to have a chat if you like - HMU @ [email protected]

Cheers,

Yanni

no suggestions, just a few thoughts:

1. you do NOT need to feel guilty for being skilled at working one on one with people from traumatized backgrounds! it's a good thing!
2. there's nothing stopping you from developing other skills as well - you're young and have so many options
3. I can tell you're both very passionate about helping people one to one and making a big difference in the world and you're feeling like there's no way to do both. That sounds really stressful.
4. it's okay to make career decisions partially or fully based on factors other than EA. you have more than one goal and that's fine: https://forum.effectivealtruism.org/posts/zu28unKfTHoxRWpGn/you-have-more-than-one-goal-and-that-s-fine

Hi Ana,

It's great to hear you are so passionate about learning and doing research! My best guess would be that you should focus on getting some real world job experience for a year or so. While you may not have as much statistical knowledge yet as you might want, I suspect it is better for you to learn them in a supportive 'real work' environment than on your own. Given that you have a PhD and soon two Master's (impressive!) I expect employers will trust they can train you up in the skills you need, so you don't have to learn them outside of a job first.

Something employers will often want to see is some evidence that you can solve their problems outside of a research/academic context. I expect it will be a lot easier for you to find a role you are really passionate about once you have some job experience, even if that means doing something that is not your dream job yet in the meantime.

Good luck!

Hey!

You might be interested in our podcast on using data science to end poverty, where we interview a data scientist at Berkeley's Center for Effective Global Action. In a similar vein to CEGA, you could check out J-PAL. 

I imagine that a few relevant things here might be: 

• Do you want to be directly applying your data science skill set, or are you happy to have a more general role? I imagine that small organisations won't have enough work of the specific type for which your skill set will be most useful for you to do that full time. So it might open your options more if you were happy to do more generalist work. 
• Your quant problem solving background might be an indication that you'd be good at some more qualitative roles, but it will be a bit harder for people to know exactly how indicative, and if someone hasn't hired a data scientist before they may not know how to interpret your background. That likely means you'd have to apply to more positions in order to have a chance of getting one, because it increases noise in the application process. 

I imagine it could be hard for organisations to really know what you'd be able to help with for the (very kind!) offer above. One option could be suggesting a specific project to an organisation that you think would be useful for them. We've got a bit of advice on how you might do that. You might also check out this site, which tries to match volunteers with projects. 

Hey; I work in US politics (in Data Analytics for the Democratic Party). Would love to chat if you think it would be useful for you.

Getting really good at sales can be valuable in a lot of careers, including the political world. Have you talked to any EAs from DC? I bet they have a Facebook group

I would definitely look into lobbying as a career route! That seems like a high-impact use of sales skills

Also, if you want to get involved in policy directly (rather than via research), an MPP or MPA might be a better fit for you rather than an MA/PhD. 

A few things I'd think about  re: MBAs from my own observations (friends who've done them etc):

1. How high are your earnings currently relative to market / what MBAs are getting? You're more experienced  than I'd say most  of the people I know who got MBAs are - will you be able to find a job that increases your earnings a lot (eg. if you are already in strategy consulting this seems unlikely)
2. What personal sacrifices will you make in a new higher earning job (ie if you switch  to IB or consulting will you be okay with the hours / be able to earn the higher salary for long enough to justify your investment)?

My take on this is an MBA is a ~200k direct investment. Plus you are potentially missing out  on opportunities in your current job to progress (ie will you miss out  on a promotion opportunity?). I'd say you'd probably want to expect ~350k extra earnings out of the MBA to justify opportunity cost + time cost of  money. From your post it sounds like this MBA will help you in role though - so that might be an overestimate. 

Additionally if you haven't read about  Financial Independance  (FIRE) that might be a good thing  for you to look into as  it would: 1) help you meet your goal of providing financially for your family sooner 2) potentially increase your ability to give for a fixed amount of income.