Equity Compensation — Top 10 vs. Bottom 10 Silicon Valley Companies

Patrick Harrington, Ph.D. — Co Founder and Chief Data Scientist, Paysa

Figure 1.Top 10, Bottom 10.
Percent Above Average Size of Equity Grant by Silicon Valley Type Tech Companies.

The dream. You’re a mid 20-something, well educated in computer science, and you head west to the golden state…seeking riches in the form of startup equity. The goal: work hard, help grow a company and ultimately your common shares are worth enough to say buy a house, stash away a nest egg, or if things go really, really well…retire.

Equity is one of those types of compensation that is typically the largest portion of an engineer’s earnings.

Here at Paysa, we mine through all types of compensation data across all private/public tech companies and build up the market dynamics from the “ground up”: through the user and their rich attributes that makes them unique.

Today, we’re highlighting the top 10 (and bottom 10) Silicon Valley tech companies that are paying the most (and least) with respect to equity grants for their employees while accounting for thousands of other features to isolate the effect of particular companies on equity pay.

What everyone is hearing lately is that Snapchat is on a tear to recruit the worlds best talent and build out this company as it heads towards building a strong revenue profile on top of its incredibly fast growing user base.

Welp, we’re seeing that they are paying…a lot to attract folks to their beach front Southern California HQ (sounds pretty good when that NorCal fog creeps deep into San Francisco and all of a sudden you’re wearing a goose-down winter jacket in July).

So inspection of the data reveals that, all else being equal, Snapchat is paying 267% above average with respect to the size of their equity grants (see Figure 1). To put this in perspective, even the behemoth, Uber (which is paying an impressive 234% above average) is beat out, here (which is surprising).

We see the usual “unicorn” suspects populating the top 10 list. For those curious, Google was 15th and pays 68% above average with respect to equity grants. Facebook (and Twitter) are the only public companies in the top 10. They appear to be continuing to incentivize their employees with large equity grants to ensure they have “skin in the game” to help them further grow their revenue and user base in developing countries.

Now, many companies especially those more established, tend to offer cash bonuses and often times higher base salaries.

Paysa has built up the market dynamics from the “ground up” at the most granular, atomic elements. To illustrate the variation in compensation of Snapchat vs. Facebook, I’ve spun up the Paysa Explorer as a Data Scientist in both Los Angeles and Menlo Park, respectively to see what I’d earn at and how. Paysa Explorer is personalized to you, so give it a spin if you’re interested to see what you’d earn at these companies.

Figure 2. Patrick’s Total Annual Compensation as a Data Scientist at Snapchat in Los Angeles, CA. Breakdown of Drivers of Equity Compensation at this Job for Patrick.

Now, inspection of Figure 2. shows what I’d likely earn as a data scientist at Snapchat down in Los Angeles. You can see, on the left, the breakdown of total annual compensation. Snapchat doesn’t pay a annual cash bonus, yet so the main drivers are base and equity (still illiquid). If I click on the Annual Equity pie-slice I descend into the drivers of why my annual equity grant is worth what it is (multiply by four to get standard total grant size). The size of the “company” driver is largely reflecting the magnitude of just how much above average Snapchat is paying for equity. Other drivers are skills and attributes associated with my title of Data Scientist.

If we pivot to say Facebook, and put me there as a Data Scientist at their HQ in Menlo Park, you can see (Figure 3) how the breakdown of my total annual compensation changes. Higher base salary, cash bonus, still a super solid equity grant and even a nice sign on bonus. If I drill down and click on the Base component of my compensation (to present some contrast), you now see a diverse range of drivers that are building up what I’d likely earn as a base salary at Facebook in this role. You see various educational components, skills, attributes of the company and others.

Figure 3. Patrick’s Total Annual Compensation as a Data Scientist at Facebook in Menlo Park, CA. Breakdown of Drivers of Base Compensation at this Job for Patrick.

We are incredibly passionate at Paysa about shedding light on the opaque landscape of the labor market, personalized to each worker. Paysa has built tools to guide you in the direction of compensation transparency so folks can “step” in the direction a positive gradient of whats best for them, professionally. Analogous to Paysa Explorer, we’ve built the ability to see 1. what you’d earn at various tech jobs and 2. quantify how good of a “fit” you are to those jobs with Paysa Jobs.

Ultimately, one should have the same transparency surrounding compensation as one does when they see a landscape of prices when they search for anything on Google or Amazon. Paysa delivers this for you and ultimately your paycheck.