Interactive Salary/Equity Chart for Jobs Offered in the San Francisco Bay Area | Hacker News Reader

Interactive Salary/Equity Chart for Jobs Offered in the San Francisco Bay Area

minimaxir.com

95 pointsminimaxir39 comments

I think it's inportant to point out the source of data is Angel List and therefore the numbers predominantly reflect those of startups.

Why is there never a chart on HN that makes me feel like I'm paid fairly?

Surely that's some sort of HN bias ...

Dare I ask whether the charts make you feel over paid or under paid?

Under paid. Always.

Hah, HN gives me the same feeling pretty consistently. If/when I leave the game industry I'll be disappointed if I have less than $500K total comp as a result of years of reading HN comments on what decent engineers should get paid.

I love this comment. I've been running my own small game studio for nearly five years in San Francisco and this resonates deeply. After reading HN for a while I constantly question my life choices work-wise.

Well don't feel too bad, we also pay $2000-5000/month for 2 bedroom apartments.[1] California also has a tax rate at the same level as Canada. Being a digital nomad you can keep the tax rate and cost of living pretty low.

But typical bigco sr. eng total compensation is around $250k. On top of that JS engineers tend to get paid less than mobile or backend engineers, but business owners make the most out of all of them.

[1] Depending how long you want to commute to work and where work is.

I too live in SF these days. Posts like this still make me feel underpaid.

Prefering small startups over BigCo seems to have been a bad choice when building my character. But I'm having more fun. Maybe.

Well it's not too late to go to a larger place :). I've found it isn't that different, especially when they are a few years before IPO. AirBNB has a really small engineering team for their size too and are very web heavy.

If I was going to do a small startup again, I would found a company. Going from 40 employees / series A -> $1 billon unicorn, I realized that I would of made more at a big co even if I was able to sell all of my vested shares.

This is a pretty good overview: http://danluu.com/startup-tradeoffs/

If you want to chat just send me an email on my profile, I'm in SF too.

For someone living in Southern Europe, what I read in HN seems positively science fiction, I learned to live with it.

With almost 10 years of professional experience now, I'm making less than what I did for an internship in the Bay Area just out of university.

There are plenty of engineering jobs in the "non-engineering" graph.

  ("Fullstack Javascript Ninja" 3% 50K)
  ("Avionic Software Lead" 6.25% 120k)
  ("Software [Developer]" 3.5% 32.5k)

This seems like it invalidates the results.

3 jobs out of 3,000 in a category does not invalidate the results and is within acceptable error (and even if there was a super-mega-ultra outlier as a result, that's why the median is used instead of the average). Although I made my best effort, it's infeasible for anyone to get 100% perfect categorization, which is why I would not have made this visualization without having a sufficiently large sample size.

I agree that a few misclassifications is not a huge problem, but it suggests a bigger methodological flaw. Looking at your source code, it seems your definition of engineer is

  grepl("engineer", tolower(job_title)) | grepl("developer", tolower(job_title)

This seems like a poor definition of engineer to use. It includes "VP Engineering" but excludes "CTO", it includes "Growth Engineers" (marketers) but excludes "Code Ninjas" (developers). Short of word2vec, I don't think you're going to be able to automatically classify people as engineers based on job title.

That heuristic is good for 99%+ of the data set (and probably higher accuracy than a word2vec approach anyways). That's more than acceptable for this analysis.

You don't even need word2vec good old cosine sim or an svm on the descriptions would classify theses. But if you're stuck with just the titles, just make some more patterns. There's not much you can do without building a simple dictionary.

Lower range for engineers than I would have expected.

This is just from angel list. So essentially just early stage startup salary ranges, presumably?

Angel List's salaries are literally a joke. It's not hard to find something like "senior full stack developer; salary: $1,000 equity 0.0%" or "co-founder salary $0, equity 0.0 - 0.05%"

It's completely useless. I can't imagine who you'd actually attract with these ads, because you literally can't pay the rent with this money and the equity for senior positions is insulting.

People that have a million in stock from a previous exit that don't need the money for a few years?

And they're really itching to work for basically charity for someone who will greatly undervalue them. Sure. I saw some unicorns by the lake the other day too.

What I wanted to do was map offers to startups (so I could at the least tag smaller startups), but the AngelList API intentionaly omits the startup name/information from the Jobs endpoint. I'm annoyed.

I was going to say, why not scrape their pages? But they seem to require you to log in to view any job postings, and even then it's some custom feed.

This is based on angel.co data, so it's woefully lowballed.

Extreme sampling bias.

Startup has opening -> Can't fill it with people in their network -> Can't fill it with people who come to them -> Resorts to Angel List posting -> Angel list posting stays online longer because they have trouble filling it -> high turnover means the job ad stays up forever or keeps getting reposted.

Great jobs tend to skew toward the left side of that funnel = sampling bias.

Pretty much. Another major assumption here is that Angel List postings are legitimate - even though some companies post "job openings" online to vacuum up resumes for a database.

Their career-wide median is just barely north of what I was offered coming off a college internship, with no competing offers or negotiation.

Same. I would've guessed mid 100s for engies, easily. Probably closer to high 100s

Nice charts, this is really cool. One thing, though - it's weird to have "researchers" not compared against engineers, since at lots of places they're functionally just two different titles for the same job. Is there a reason for that choice?

Equity percentage graphs of a large number of companies, with no additional information, are completely useless information. I'd much rather have 0.01% of Google than 1% of whatever your startup is.

I'd be curious if the distribution of salary data from H1-B filings was more or less the same. Anecdotally for brand name companies, eg Netflix, the selection bias of Angel List data to the lower end seems to be confirmed. The database publicly searchable and I had seen a visualization once but can't find the link.

http://h1bdata.info/index.php?em=NETFLIX+INC&job=SENIOR+SOFT...

I'll weigh in; work (remotely) for a startup in the Bay Area, around 100k salary with .5% equity.

I'm hoping to have more equity granted to me in the form of options in the coming months as the company turns a profit.

Otherwise, life is good.

Maybe the ranges are more useful in the Bay Area. For Berlin I saw some companies putting €30k - €100k because it's required on Angel List.

Pathetic amount of equity, 0.1/0.02%. Startups should be ashamed. Your greed, your loss.

If you have, say, 200 employees, how much equity do you suggest offering?

Of course, they should get 10% each. Don't be a greedy bastard.

These are angelList companies so the safe assumption is there is significant less than 200 employees. How many 200 person startups are their relative to 1-10 person startups, 1 out of 100 or more. Salary is low too so safe assumption.

I would cut out all the data with equity above 2% as the signal there is probably very noisy.

Interesting data - what do the colors mean on the chart?

They're just a visual aid to list the change in salary. It works well with the background of the hover tooltip.

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