My experience on the tenure-track job market
Published:
Before anything substantial
This casual write-up is heavily inspired by Prof. Rui Bai at George Mason, who had a similar post in 2020. I think I should document the process before my memory, excitement, and frustration eventually fade away.
I have to make the same disclaimer as Rui: this is based on a sample size of 1 and mostly on the statistics and computer science (CS) tenure-track (TT) job market. I did apply for roles in the US, Canada, EU, and UK. I was only able to get interviews and offers in the US. I will focus more on the experience side, especially on how it feels at each stage, and less on instructions for what to do.
I wrote the post and used Prof. C(hatGPT)’s help with grammar and flow.
Why academic job market?
This part is not about whether to choose academia, only whether to go on the TT market. The tough call between academia and industry is postponed, both in my real-life experience and in this post. To be totally honest with readers, I was never in the camp of academia at all costs, especially because I have an interest in quant finance, an industry that has stellar pay and, in many places, a surprisingly reasonable work-life balance.
The reason for me is that I think intellectual freedom is a real thing that is at least worth a serious try, and I wanted to understand the job market. The latter was enough to justify going on the market, and the former, if it works out, is simply great. So at least in August 2025, these two pillars prompted me to go on. Another minor reason behind the decision is that my time at Citadel Securities in summer 2025 was not totally aligned with how I work: I was handed a dataset without knowing what it was. I was able to get something to work, but I was kept away from the full story. This experience, at that time, made me think quant finance was like that everywhere. I remember my manager was not quite impressed when I said my main drive is to know how things work and how to do things, rather than to win. This made me think I should at least give the TT job market a try.
Did I try anything else? Absolutely. In fact, I went on all the job markets where I thought I could reasonably get interviews, namely TT faculty, postdocs, quant finance, and tech research. They are all quite different and worth their own posts. I was reasonably successful in most of them except tech research, where I was only able to land a single interview with ByteDance and was not able to get an offer from them.
When to do what
What I did. I did the search in a rush. Ideally, the process should start quite early. For me, it should have started in May 2025 (I was on the market for a Fall 2026 start). However, I was interning in finance and until probably early July I thought I would just stay in quant. The decision was made in early August, and I essentially wasted the entire summer when I could have been preparing materials.
Regardless, I went on and the first step is submitting your materials. (Well yes, you need to prepare them first.)
Some places might say something like applications are open until filled but still give you a date saying applicants will receive full consideration if they submit by that date. Treat that date as the deadline and submit by then. My earliest deadline was from the Cambridge ML lab, on Sept. 20, 2025, and I did not start preparing materials until the end of August, so I had essentially only 20 days for everything. That was not ideal.
In chronological order, I made the call that I would give the TT job market a try at the end of August 2025. I prepared materials until around mid-October, when many places had closed, so I submitted half-baked materials there. After COVID, the interview process usually involves a first-round, 30-minute Zoom interview, which I will elaborate on later. These happened for me in early to mid-December 2025 for most places. I did get one invite in April 2026, which is somewhat unusual. Onsites (or “fly-outs”) happened for me mostly in January 2026, and I had two of those. The April Zoom eventually turned into a fly-out in late April as well, but I think this is quite late in the cycle. In general, CS is later than statistics, and managing the two can be challenging. I heard back from the first onsite the day after I was back, as I was the last one being interviewed, and for the other one I heard back several weeks after it happened.
In parallel, most of my quant interviews happened Nov. 2025-Jan. 2026, a period with lower activity on the academic-materials side, and the hope was that offers would land at roughly the same time as academic ones. I ended up having both active academic and quant offers in Feb.-Apr. 2026, so it worked out for me.
One annoying part about the TT market is that the timeline is very long and messy, with things overlapping a lot. As mentioned, the first application deadline I had was Sept. 20, 2025, and the last one I submitted was not due until Jan. 12, 2026. By the time the last application was due, I already had a handful of interviews, many rejections, had been ghosted by many places, and was maybe 20 days away from getting my first offer.
What should be done differently. One should start in May, use the summer to get materials ready, and apply during the fall. In the meantime, while applying, one can prepare the job talk and related things, or do part of it in the summer as well.
Materials
There are many resources out there about what to prepare, but for most places you need:
- Almost always needed
- Cover letter
- CV
- Research statement. Some places say 4 pages, some 3, and some combine it with teaching. Read their instructions.
- Teaching statement
- Reference letters, 3-5. Some places require one about teaching, but I heard that people without it can still get jobs that require it, so I don’t really know.
- Less common things
- Sample papers: this is not that uncommon; about half of the places I applied to wanted them
- Teaching dossier: evaluations, sample syllabi, etc.
- Diversity statement: more common in Canadian places
- Mentoring statement
- Service statement
Just in case you want to see mine, they can be downloaded here (large zip file hosted on GitHub).
Keep track of things and be prepared for potential mistakes
I had a Google Sheet to keep track of deadlines, letters, etc. In hindsight, I should have paid that 50 bucks to Interfolio so that I did not need to bug my letter writers all the time, but it is your call. Color-coding status is a good idea, and I think everyone from my group on the market did that.
One thing I want to mention is that you can, and probably will, make mistakes. I submitted my Cornell CS cover letter to UCSC Stats, and UC’s application system does not allow changes after submission. The last thing you want to do when this happens is panic: just send a polite email to the department contact in the system, ask them to update the cover letter, and move on. As long as you fix it before they start reviewing, people probably will not notice.
Interviews and job talks
Prepare early. Practice a lot. That is all I want to say about job talks. Your advisor will probably have a lot to say about how. One thing I want to mention is that different people have quite different opinions on what a good talk should look like. For example, my advisor really does not like having equations (neither do I). But some people will say that without any math, your talk can feel non-serious, which I also get. I ended up having some equations, but not a lot, and there were no proofs. Also, I only talked about a single paper. Some people like that; some don’t. Find the approach that makes the most sense to you, and be aware that the audiences are likely not from your area, so giving a lot of concrete examples definitely helped me. (I mean, I branded myself as a sorta science-first person, so I do need actual examples.)
Interviewing is chill, at least for me. I found it nice to just talk to people about their research and your research one-on-one, and ask questions about their life, culture, collaborations, etc. After all, you give a talk at the department and hopefully make a handful of friends.
At least to me, the interviews, especially the onsite part, were the most enjoyable part of the process. And I hope that will be the case for you. Go and enjoy the free trip, meals, and meetings; make some friends and potential collaborators.
Frustrations and stress
This is the part I want to write the most as I find people don’t write nearly enough about it.
The process is EXTREMELY FRUSTRATING to everyone I talked to, probably except for that single person who got every single offer that year, and that was definitely not me or anyone in my immediate circle.
The timeline is very overlapped: you will receive rejections when you still have to submit applications. You will get interviews in the middle and get ghosted even if they say they will let you know: one school in Texas told me during a Zoom interview in early December that they would get back to me by Christmas, and I never heard back from them.
The process is very opaque: there is no way for us to know what is going on on their end. The department might have a very specific need, but we will never know. Among the places where I got positive results, one wanted someone “Bayesian but not that Bayesian” who could collaborate with astronomy or genomics, and ideally both. Another specifically wanted someone who does ML and ecology (and ideally has field experience). On the negative side, I applied to a bunch of places that, in the end, I heard wanted someone who does pure theory, etc. One place where I went onsite in PA probably really wanted someone who could teach optimization. Of course I did not get it. The timeline is also very opaque. Again, you might hear some places say they have an ideal timeline, but it may not materialize on your end. You will not know if you got ghosted or they are delayed; both happened to me.
You also don’t quite know who makes the decision unless you know the politics in the department. I have a friend at UNC who told me a lot about it — and I did not get the job after all, so that information was not all that useful for me, but it is also frustrating to know that they can make decisions quite arbitrarily. One of my biology friends once even said we should just Zoom-interview people and do a lottery. I still buy that.
Peer pressure is real: you will have friends on the market at the same time, even from the same group. This is not a good feeling, no matter whether they get more or fewer interviews. I felt really bad when my friend got a Cornell Stats interview, which was my top choice at that time. I also did not know whether I should keep him posted on my progress, but he clearly did not want to keep me posted, or at least not actively.
You are not alone! We all felt this way. Academia is a weird place and has a lot of nonsense. The job market is definitely one of them.
Negotiating
Ask for money, compute, course releases, and potentially a deferral if you want to do some random stuff for a year or a postdoc. There are many resources out there for this, and your advisor will be a great resource as well. It might be awkward to ask for more money, but do it. It is business, and we should always try to get the best deal. The worst thing that can happen if you ask for more money is that the chair comes back and says, sorry, the dean cannot approve it. That’s it; you are still friends with the chair.
Making the tough call between academia and industry
In mid-March I had TT offers and quant offers ticking, so I had to make the tough call that I had been postponing for the entire job market year. I lost sleep and found myself depressed. Yes, ironically, without any offers one can be depressed, and with multiple offers one can also be depressed, especially when the offers are apples to oranges. It is not totally unreasonable to be depressed in hindsight: both options (quant and professor) were great options. Turning down either of them would be a loss, and humans are more sensitive to loss than gain. The decision was made using a regret-minimization argument: it is easier to go from faculty to quant than the other way around, and money can wait, at least while I am still not that old.
Talking to people is great at this time, in my opinion, but you also need to remember this is your life — someone who hates academia will not be the person who lives the quant life for you, bearing the fear of being laid off, etc., and someone who found meaning in academia will not help you handle the pressure of tenure and funding, as well as the financial stress being an underpaid professor.
How did I make the call, after all? And what are the differences?
But in general, what made me make the call was regret minimization: I want to know how academia works from the other side. To me, it is yet another experiment of life that I think is worth the salary difference. Some companies were also open to keeping in touch and seeing what happens, which helped a lot.
These are the things that helped me:
And here are some differences:
Pay and stability
I cannot say much about the tech industry, but I can say a bit about quant finance vs faculty. First and foremost, quant finance pays way, way more, with some tricks related to bonus vesting. One NYC-based offer I got had a ~250k base and ~500k bonus, but that 500k would not vest in the first year. It was split into a 2-3 year vesting schedule, so yearly cash flow was not as high as it might look. Some firms can, and will, fire you if you don’t perform, around year 2 before you get the bonus. And the bonus can depend heavily on the performance of the firm, the team, and you.
On the other hand, faculty pays way less but is relatively more stable. One offer I got from an R1 paid 135k for 9 months, and you really cannot assume you will always be able to get your summer salary, so it is quite strained, but much more stable. You got job security for at least 6 years before tenure, which is rare in the current market.
“freedom”
In quant, you are doing research about the market, and the goal is simple: making money. As faculty, on the other hand, you get some freedom in what you want to work on, with a big footnote saying: as long as you get funded. Remember, your summer salary depends on funding, so how much you get paid depends on how much funding you get, and tenure does as well. So it is not all that free after all.
IPs and visibility
Both places have IP constraints, but quant is way more secretive than faculty. Quants pay that much to make sure you do not leak what you figured out in the company. So one big trade-off is that you must become nobody in the quant world. You have to give up some publicity — this can be a big change for an academic, where we need visibility. One offer I got from quant had a lifelong NDA on what I worked on there, and some places have IP clauses so broad that they essentially all statistics are covered.