I lead research at one of the most prestigious trading firms. I’m interested in meeting people doing thoughtful, independent work on systematic trading (1mn horizons up to months), including those who haven’t followed the usual industry path or have struggled to get into the industry regardless of their track.

The proposition is straightforward: show me what your model does, not how to reproduce it. If the work is compelling and meaningfully different from what we already do, I’d be interested in discussing a role on our team.

For an initial conversation, I’d be looking for:

• A high-level explanation: what you trade, your typical holding period, and the broad intuition behind the approach.
• A sample of historical daily positions or portfolio weights, alongside returns if available. An anonymized model portfolio is fine; no account statements or live positions needed.
• Some context for the results: backtests, paper trading, or live; the period covered; and assumptions about transaction costs and leverage.
• Your assessment of its weaknesses: when it struggles, what could invalidate it, and what you’re still trying to understand.

I’m not asking for source code, exact signal definitions, proprietary datasets, or anything belonging to an employer, client or yourself. Please only share work you own and are comfortable discussing.

I care more about the quality of the reasoning, honest evaluation, and a genuinely different approach than a spectacular equity curve.

There is genuine hiring interest if we find a strong fit and I'm happy to be providing insights about the work.

If that sounds relevant, DM me a short overview first. No need to send detailed research or position history in the first message. I’m happy to share more about myself and the team before you decide whether to take it further.

BTW my profile has been verified by a mod.

How do quants get a complete and accurate security master? Do they buy it? Is it something that each shop provides to their pods or does it come integrated with trading software like Bloomberg?

Curious how people here are using AI in quant research. Have you asked it to brainstorm alpha ideas, and did anything useful come out of it?

I’ve been experimenting with it, and the quality of the ideas has seemed better than what I get from my manager on a central team. It is concerning for various reasons, LMAO.

Hi, I've been working at one of (DRW, IMC, SIG, Optiver) as a QR for 7-8months now and I'm looking to eventually start looking at (Jump, HRT, JS, Citsec) within a year or so, (I'll have about 1.5yr at that point). I was wondering how different are experienced QR processes than new grad?

I am 33, ten years of work experience. Started at mlp in march of this year but my salary is below the market rate. Recruiters tell me mlp eventually starts paying very well once you’re there for some time how true is this?

I’m in between jobs, looking for new roles, and I spent several months building A LOT of infrastructure for a stat arb trading system, along with a strategy at the end. I am planning on reaching out to my network and pitching what I’ve built to some firms, my goal is to come in as a Senior QR or sub-PM that can implement what I’ve done there and continue building off it. I want to know how IP would work in this case, and what’s the best scenario I can achieve for myself. I may end up at a pod shop or maybe a shared manager platform.

Any QRs here working at trader-led prop shops where they ask you to build signals and strategies, but it feels like everyone above you is betting against you?

The attitude feels like: “If you were actually good, you’d already be at a systematic shop or running a pod.” Meanwhile, they want you to keep producing alpha for them. You take something from idea to research to production, and somehow it becomes the trader’s strategy. Your ownership gets downplayed, with the usual carrot of “more opportunities later.”

I sit right next to the traders on our desk, and whenever my algo loses money, there are jokes at its expense. Most of the time when it makes money, though, it’s dead silence.

I get the conflict for individual traders. They need to protect their seat and prove they’re indispensable. What I don’t get is why trading heads and quant heads, often former traders, reinforce it too. Shouldn’t they back whoever makes money?

Not saying execution and risk management don’t matter. But has anyone actually gone from “research support” to meaningful ownership in this setup, or is leaving usually the answer?

Is this just prop trading culture, conflicting incentives, or am I missing the political game being played higher up?

Would love to hear from QRs who’ve dealt with this, or traders willing to give an honest take.

Hello - curious people have views on the best way to apply for jobs within the leading quant funds. Do recruiters have a benefit over internal referrals? Does it differ between multi-manager, prop, asset manager, boutique hedge funds?

I have seen at least the recruiters are more aggressive in following up, getting feedback, sharing past experiences. Though not sure if firms actually prefer internal referrals over external recruiters.

As a quant, do you need to handle stakeholders’ expectations? Do you need to explain your findings to non-technical business people, “sell” and defend your idea, manage their expectations and address their doubts?

I applied for MSCS in last bachelor year in selected universities, but did not get in. My original plan was anyways to apply masters after an year of working as a Quant Research to be able to fund it. I do not have a publication, but I believe my profile is decent on other counts. However, after 1 year, I got cold feet and didn't apply. Now, I am working as a Quant Researcher at an Indian HFT for 3 years. The pay is good, but the learning is slow (because of firm) and I am having FOMO about AI. What are the views of r/quant regarding continuing in Quant versus trying out graduate studies?

What are the most widely used tree-based models in industry today, and how should teams choose between options like XGBoost, LightGBM, CatBoost, and Bayesian approaches? In practice, which models would you recommend for different use cases, and has there been a meaningful shift toward Bayesian methods or do gradient-boosted trees remain the industry standard?

Was wondering if anyone has read this latest book by Stefan Jansen - "Machine Learning for Trading: A disciplined workflow from research to live execution, with nine case studies and AI agents". It seemed to have great reviews online, so I started to work through it but I find it impossible to read - the entire thing feels like AI slop. The way the sentences are structured are so obviously AI generated - it's difficult to explain but easy to spot when you read it. The accompanying notebooks are also very obviously AI generated. Pretty disappointing for a book in this price range...

Can anyone recommend similar books that aren't AI generated? Or if anyone has read this entire book, is it worth sticking with?

Let us know your worst/funniest interview experience

Some friends' funds are making a killing while others are getting killed. It is obvious that we are looking at a market condition drastically different from first half of the year. what are your thoughts on this

Hoping to hear experiences from people working under the broader XVA desks, is it still as big considering a lot of transactions are centrally cleared? Are the charges tricky to calculate? Is the work stimulating and comp competitive?

I am a NG (started in Jan.) at a pod shop doing factor-neutral MFT stat arb in equities, ie. the worst performing asset this year by a WIDE margin. Basically flat this year and my PM really likes me and trusts me (I am like a quarter of his US alpha on a >1.5bn GMV book), but obviously vibes do not pay the bills.

Not really sure what advice I'm asking for, but am curious how other juniors deal with subpar performance early in their career. I can't say that it's my fault (literally no alpha these days) and we are faring much better than many other pods in the industry. But I do have the feeling of not doing enough, kind of like this will stunt my growth because I don't have strong PnL to my name yet (plus my bonus this year will be trash).

Thoughts?

Let go after 1.5 years. First job out of uni, QR at a hedge fund in London, still have a few months of garden leave.

This was partially for performance; I had some negative feedback, worked hard to get back on track and from follow-ups it sounded like I had addressed it.
My feedback when I was let go was essentially "improved but not quite enough, and not the best fit communication-wise" which is fair enough.

What is the best way to handle this in calls with recruiters/interviews? Half the posts look like they're saying to be completely honest from the start, which seems like reducing my optionality for no reason.

My quant friends at other firms have pretty unanimously said "just say as little as possible", but none of us are anywhere near being hiring managers so I was hoping to get some more experienced input.

Honestly pretty happy to be moving on from that job, but don't want to shoot myself in the foot for no reason. Old/throw away account for obvious reasons.

“Seem” is important, it’s a sample of me talking with three commodities traders at major banks.

But on general they don’t seem to manage more flow or bigger books compared to traders in utilities / shippers but tend to work longer hours, from 08:00 to 19:00 .

It’s quite a lot, the wlb for FO roles seems better in gas / power shops. And it’s not like politics doesn’t play any role at BP or Shell.

I’m a QR with ~5 YoE with an asset manager, working on low frequency quant equity strategies (think systematic equity factors, quarterly rebalance). I want to get into mid frequency equity strategies with holding periods of days to weeks and would appreciate some advice from people who are already in this space.

I’ve been experimenting with some basic reversal strategies for interest. One thing I wonder is when mid freq QR test new signals whether they strip out equity factors like momentum from the signal? If you had a daily or weekly signal, this would mean having to orthogonalise the signal daily would be quite intensive. Or is this done on some industry optimiser like Barra or Axioma. Any thoughts here?

I am a C++ developer and just started my 1 year non-compete.

Curious what others here have done during this time. I am thinking of exploring ML inference optimization or some other technically challenging work, preferably involving C++.

Would love to hear what you guys worked on or explored during your non-competes (I don't think I can take break for more than a couple of months).

Optiver borrowing a lot of money, interesting that they decide to go with external debt financing vs reusing some of their revenue/profit? I'm not sure how prop trading firm typically raise money

Curious to hear how different quant shops, prop trading firms, and funds approach return targets and risk expectations right now.
Given that many HFT firms and smaller-scale systematic funds regularly push triple-digit annual returns on capital, combined with the fact that passive benchmarks like SPY have also delivered strong performance, the opportunity cost and return landscape feel quite competitive.
For those working in the industry:
What is your firm's internal target return (or Sharpe/Sortino ratio target)?
For those managing external capital or dealing with LPs, what are their realistic return requirements and drawdown tolerances given today's market alternatives?
Would love to hear how different strategies (HFT vs. statistical arbitrage vs. directional quant) approach this.

I’m trying to build a picture of the systematic commodities landscape, coming from a different asset class. I know the big multi-strats and prop shops (Citadel is well known for power, for example), but I’d like to understand the structure of the space.

- Which firms or desks are the leaders, and in which markets (power/gas, crude and products, metals, ags, etc.)?

- Roughly how many teams are running highly systematic strategies focused on commodities?

- What do they typically trade (outrights, spreads/curve, cross-commodity, options) and how do the approaches differ between firm types?

- Are there smaller or lesser-known shops that punch above their weight?

Even a partial answer on one sector or one type of firm would be really useful. Thanks!