Is your employer paying you what you’re worth? It’s an important question, and one that shouldn’t remain a mystery any longer.
Paysa, provider of market salary data, today announced that it has raised $4 million in seed funding from New Enterprise Associates (NEA), Milliway Ventures, and other private investors.
Right now specifically focused on students and professionals in software, data science, or IT fields, Paysa allows individuals to explore several data points around what their compensation should be, including base salary, bonuses, and annual equity. The service uses several different factors to determine this, including the company, career level, and title.
It doesn't just empower engineers to fight for raises, but also to make informed decisions about moving onto a new job, focusing on honing broader skills, or deciding on a location move.
“Paysa was born out of the frustration with how little data employees have when it comes to salary negotiation or where to invest their time to add value to themselves, professionally,” said Chris Bolte, Paysa’s co-founder and CEO, in a prepared statement. “With Paysa, we aim to empower individuals with all of the data they need to make an informed salary decision and help move conversations with employers from an opaque one, to one of transparency and clarity.”
The Palo Alto company certainly isn’t the first to offer data of this kind.
Glassdoor, the site where past and current employees can leave reviews of companies and managers, also collects data around compensation and benefits so that it can provide a snapshot of salaries at different employers. The service doesn't limit itself to any field (as Paysa does today), so, at a glance, you can see that a financial advisor makes an average of $53,448 at USAA.
Payscale is another company that’s more similar to Paysa in that it focuses exclusively on salary data. In addition to providing a salary report to individual, PayScale offers compensation SaaS software for companies to determine how much to pay their employees based on geography, role, and experience.
Paysa says it’s different than these and other competitors because, in addition to factors like education, location, and title, the company “processes more than 10,000 variables and 30 million salary points” in its salary projections. That’s a bit vague, so I reached out to the company to see if they can clarify what those “variables” and “salary points” are exactly. Here's what they said:
"The machine learning technology that powers Paysa extracts 10K+ attributes of career profiles across professional experience, expertise areas, education, locations, titles, companies, etc. from 90M+ career profiles. Each of these 10K+ attributes / variables has an inherent value that they bring to someone’s profile leveraging the 30M+ salary data points that are connected to these profiles. Paysa’s matching technology and algorithms assign a value to each of these attributes and then builds a users market salary based on the summation of all of those data points.
"The 30MM salary data points come from 4 sources publicly available data, directly from companies, recruiters and users. By combining these 4 data sets together, our algorithms are able to triangulate the accuracy of the data sets to deliver accurate predictions to our users."
The company says it will use its new funding to expand beyond engineering into other professional categories as well as to support international launch.