1/ How the hiring game is like trading, and vice versa.

A thread. 👉👉👉
2/ Most of what I talk about here is trading, but one of the things that pays my bills is helping companies get better at hiring.

I don’t usually talk much about that.

Mostly because the audience for that stuff is… niche.
3/ But it’s become clear, over the years of helping clients hire better, that a lot of what I’m teaching is trading skills and mindsets.

Here’s what I mean...
4/

A. Hiring is matching. Just like a trade. There’s a labor seller and a labor buyer, and the goal of a good hiring process is to make sure both sides are happy with the trade.
5/ In particular, if either side is unhappy they can DK the trade.

Busted hiring trades are *expensive* so we want to avoid that.
6/

(No, you argue! Plenty of companies do hire-and-fire and it works for them.

Yes true, but it only works in spots where labor is fairly undifferentiated. With knowledge work hire-and-fire creates a culture where it’s very very hard to capture valuable IP. But I digress...)
7/ Ok, so how do we make sure we have a match? There are two components from the employer side:

- Evaluating whether the person is a match.
- Signaling to the *right* person that this is the place for them.
8/ This is harder than it seems, and you see lots of companies play games.

- Artificial hoops to jump through
- Worthless “culture fit” interviews
- Or making a point to show the rock-climbing gym next door that everyone belongs to.
9/ But if you take one thing away from this thread, either as an employer or as a job-seeker, it’s this:

“Hiring processes are good in proportion to how well they simulate the actual job.”
10/ This is your north star, the thing you always have to keep coming back to.

The better you simulate the job, the better your matches will be. For two reasons:
11/

- It gives the employer a better read on the candidate (component 1).
- Equally importantly, it shows the candidate what the job’s about (component 2).
12/ What does this mean in practice? First, it means getting rid of some things:

- Whiteboard coding for devs. How about you sit them in front of an actual, you know, computer if you want them to write code?
13/

- That pointless lunch hour where you talk to the candidate as though you were a friend. You’re not friends, and the read you’re getting in that hour is worthless. Do Structured Behavioral Interviews instead.
14/

- Stop lying about the job. If the job is writing shell scripts to munge data and shuttle it around, don’t call it a Machine Learning Scientist job! Etc.
15/ Think like a quant trader: the interview is your chance to backtest your hire before you run it in production.

Sure, ignoring borrow costs makes it look better in the backtest, but is it going to make $ in prod?

How about we build a better sim...
16/ Ok, that takes care of (A) Matching. On to…

B. Figuring out value.
17/ Lots of companies are completely schizophrenic about what they need. Lots of BS like “we only hire A players”, when the facts on the ground are completely different.
18/ And the reason they’re nuts is because they don’t really know the value of a hire. So here’s a back-of-the-envelope model:
19/

- Say you pay a person $120k per year.
- All-in cost to the company is ~$180k.
- Assume you’re running 50% gross margins.
- So, we need $360k of revenue for that person to pay for themselves.
- Question: does that person provide that value?
20/ If the answer is no, you need to re-think some stuff. Almost no company I talk to even tries to do what I just did here. Doesn’t even occur to them.

But it’s critical if you want to know what to pay people.
21/ Lots of hiring managers complain they can’t get the talent they need for what they’re willing to pay.

Well, that’s not a hiring-market problem, that’s a *you* problem. If you can’t get the value you need for what you need to pay to get it… you need to... just stop.
22/

“We only hire A-players.”

Uh, I hate to break it to you but a truly A-player developer with 5 years experience is making >$500k per year.
23/ How about we hire what-we-need-players instead?

99% of companies don’t need superstars in every seat.

Get a couple of really good people, often founders, and a bunch of good-enough people who get the job done, and you’ll be fine.

It’s software, not rocket science.
24/ Doesn’t sound sexy, but that honesty with yourself and with your candidates is going to get you better hires.

How?

Well, imagine you do build a process to try to hire superstars, but have no chance of getting them. An analogy...
25/ Imagine I build an HFT trading system but I’m the slowest guy out there. Which trades am I going to get to do?

The bad ones.

I can’t compete in that space, so I shouldn’t try.
26/ I should try to do something else, something that’s more well-suited to my skill-set.

At least then I have a shot at making money.

And if there’s nothing at all, then I should close up shop.
27/ Same in hiring. Stop trying to build an HFT-strat hiring process.

You can’t do it. You don’t have the metaphorical FPGAs, you don’t even know what colo is!

So build something else. Harvest some risk premia: make it about the business, the team, etc.
28/ Ok, enough for now. We’ll see how much this resonates out there with people, and maybe I could talk about the game from the candidate side.

It isn’t as interesting and there’s a lot of info out there. But if there’s interest...
29/ I was inspired to talk about this by @KrisAbdelmessih's recent newsletter on pay for traders.

mailchi.mp/3313ea5fbe52/w…

Also recent discussions with @RockshotJ and others.

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More from @AgustinLebron3

16 Jun
1/ I immigrated to the US 20 years ago, and I don't regret the decision. The people, the opportunities. It really *is* a wonderful country.

But downsides exist and they can basically all be summarized by the leafblower.

A thread... 👇
2/ What is a leafblower? It's a motorized wind generator that moves light outdoor particles (leaves, twigs, dirt/dust).

Facts about the common leafblower and its typical use:
3/ It's gas-powered with a 2-stroke engine.

That means it's incredibly loud and incredibly smelly. You can't mistake the odor. It's an crappy-machine solution to a pseudo-problem.
Read 8 tweets
2 May
1/ Reading @nope_its_lily and this hit hard:

"In all honesty, most finfluencers have pretty shit takes on the market. It kind of arises based on the mismatch between the skills required to actually trade and the skills required to market oneself."

nopeitslily.substack.com/p/a-polemic-an…
2/ That statement is insanely and ridiculously correct.

I think everyone who has other high-value uses of their time goes through the same thought process.

"Why am I doing this?"
3/ I mean, if you wanted to read and learn from #fintwit, you could do so without posting.

If you're not selling anything (or trying to raise AUM which is the same thing), it makes very very little sense.
Read 9 tweets
20 Apr
I just answered an emailed question. I suspect @KrisAbdelmessih @SinclairEuan @therobotjames and others get these too.

"I'm a smart engineering/CS/math student/graduate. How do I get into quant trading?"

A thread. 👉

1/n
2/ I'm going to preface this by asking an important question:

Why trading?

Almost every outsider has an idea of what trading is that's pretty far from the reality. It's not "deploy cool ML models on gigabytes of data". It's:
3/
- Do I have enough cash margin in account JP44315A?
- Why does the data format disseminated by broker X suck so much with this new update?
- How do I optimize my tax footprint?

And a thousand other little annoyances. Plus:

- Am I about to incinerate $ somehow?
Read 10 tweets
2 Apr
1/ A short thread about priors.

- What are they?
- Why do we need them?
- A few specific priors I hold.
2/ Priors are supposed to be "beliefs you hold before seeing the data".

Taken at face value this is crazy. You've been collecting data since the day you were born.
3/ But what we usually mean by priors (in a non-technical sense) is "what is your default assumption".

You may object "Ah, I don't hold any assumptions until I see the data."

That's dumb. (A) You do actually, and (B) you couldn't function in the world if you didn't.
Read 12 tweets
31 Mar
A book review: London And The 17th Century

amazon.com/London-Sevente…

by @margarettelinc1

1/n
When Elizabeth I died, noblemen had to make a huge show of her funeral in order to prep people for the accession of James I (James VI of Scotland).

With modern eyes, it’s cool to see how critical the “show” was to a government’s legitimacy. Government meaning the king, obv.

2/
This wasn’t some unnecessary extravagance. Shutting the city down for a day or two for the funeral procession was a critical part of establishing the legitimacy of the next king.

Oh and by the way, yes James II really was a horrendously bad king.

3/
Read 18 tweets
25 Mar
1/ Musings about variance in trading, in sports, and in life.

A thread.
2/ Why does poker get played for big $ but chess (mostly) doesn’t?

Because of variance.

In chess, if you’re rated 1800 ELO and you’re playing someone rated 2000, you pretty much know exactly your P(win) and P(tie). (It’s 15% and 19%, go check).
3/ There’s no sense in betting for two reasons:

- A wide spread of ability directly creates wide spread in outcome. A 2400 will NEVER lose to an 1800.
- All these probs are pretty much known. $ gets traded when people disagree about probs. No such thing exists in chess.
Read 21 tweets

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