Data Science Salaries in Seattle, WA

What is

Data Science

?

Data Scientists analyze complex data to uncover patterns and insights. They use statistical methods and machine learning to solve business problems. Their work drives innovation and strategic decision-making.


Data science professionals develop data models, perform data mining, and communicate findings to stakeholders.

Common titles in 
Data Science
  • Data Scientist
  • Associate Data Scientist
  • Junior Data Scientist
  • AI Data Scientist
  • Senior Data Scientist
  • Lead Data Scientist
  • Staff Data Scientist
Salary range for 
Data Science
 (
P3
)
 in 
Seattle, WA
Interested in salary information for other levels?

Decoding job levels: What is a 

P3

?

Pave’s job levels are denoted by their track (P for Professional, M for Management) and their hierarchical level, as denoted by a number. The higher the number, the more senior the role. There are 10 individual levels, broken down as:

Management: M3, M4, M5 & M6
Professional:
P1, P2, P3, P4, P5 & P6

For a full explanation of Pave’s approach to levels visit our FAQ.

Salary comparison for 
Data Science
 (
P3
)
 by city

Want to compare salaries across different cities? Here are the average salaries for Data Science in major metros across the United States. Ready to view additional percentiles or Data Science levels?

Los Angeles, CA
$
115000
$
144230
$
172677
New York, NY
$
140000
$
164000
$
190000
San Francisco, CA
$
146294
$
170600
$
200000
Seattle, WA
$
137500
$
165000
$
191000
P10
114384
P25
137500
P40
158000
P50
165000
P60
173300
P75
191000
P90
204012
Interested in more salary insights like equity comp or international benchmarks? Book a demo with our team -->
(function (h, o, t, j, a, r) { h.hj = h.hj || function () { (h.hj.q = h.hj.q || []).push(arguments) }; h._hjSettings = { hjid: 2412860, hjsv: 6 }; a = o.getElementsByTagName('head')[0]; r = o.createElement('script'); r.async = 1; r.src = t + h._hjSettings.hjid + j + h._hjSettings.hjsv; a.appendChild(r); })(window, document, 'https://static.hotjar.com/c/hotjar-', '.js?sv='); !function () { var analytics = window.analytics = window.analytics || []; if (!analytics.initialize) if (analytics.invoked) window.console && console.error && console.error("Segment snippet included twice."); else { analytics.invoked = !0; analytics.methods = ["trackSubmit", "trackClick", "trackLink", "trackForm", "pageview", "identify", "reset", "group", "track", "ready", "alias", "debug", "page", "once", "off", "on", "addSourceMiddleware", "addIntegrationMiddleware", "setAnonymousId", "addDestinationMiddleware"]; analytics.factory = function (e) { return function () { var t = Array.prototype.slice.call(arguments); t.unshift(e); analytics.push(t); return analytics } }; for (var e = 0; e < analytics.methods.length; e++) { var key = analytics.methods[e]; analytics[key] = analytics.factory(key) } analytics.load = function (key, e) { var t = document.createElement("script"); t.type = "text/javascript"; t.async = !0; t.src = "https://cdn.segment.com/analytics.js/v1/" + key + "/analytics.min.js"; var n = document.getElementsByTagName("script")[0]; n.parentNode.insertBefore(t, n); analytics._loadOptions = e }; analytics.SNIPPET_VERSION = "4.13.1"; analytics.load("0KGQyN5tZ344emH53H3kxq9XcOO1bKKw"); analytics.page(); } }(); $(document).ready(function () { $('[data-analytics]').on('click', function (e) { var properties var event = $(this).attr('data-analytics') $.each(this.attributes, function (_, attribute) { if (attribute.name.startsWith('data-property-')) { if (!properties) properties = {} var property = attribute.name.split('data-property-')[1] properties[property] = attribute.value } }) analytics.track(event, properties) }) }); var isMobile = /iPhone|iPad|iPod|Android/i.test(navigator.userAgent); if (isMobile) { var dropdown = document.querySelectorAll('.navbar__dropdown'); for (var i = 0; i < dropdown.length; i++) { dropdown[i].addEventListener('click', function(e) { e.stopPropagation(); this.classList.toggle('w--open'); }); } }