Data Scientist Salary in Seattle 2026: Complete Guide

Seattle has quietly become one of the best cities in the world to be a data scientist. While San Francisco still claims the highest absolute salaries, the combination of Amazon’s insatiable demand for data talent, Microsoft’s AI research investment, and Washington state’s zero income tax means Seattle data scientists often keep more of their paycheck than their Bay Area counterparts.

This guide breaks down exactly what data scientists earn in Seattle in 2026 — by experience level, by employer, and after taxes — plus the skills that move you into the top quartile.

See current Seattle data scientist salary data →

Seattle Data Science Market Overview

Seattle’s data science ecosystem is anchored by four major forces:

Amazon employs more data scientists than any other company in Seattle — across Amazon Retail, Amazon Science, AWS, Alexa, Prime Video, and Amazon Advertising. The scale of Amazon’s data problems (pricing, logistics, personalization, fraud detection) means constant demand for data scientists who can work at enormous scale. Microsoft runs one of the world’s largest AI research organizations from Redmond. Microsoft Research, the Azure AI platform, LinkedIn (now Bellevue-based), and Teams data science teams collectively employ thousands of data scientists and ML engineers in the greater Seattle area. Meta has a substantial Seattle engineering hub focused on ads infrastructure, integrity, and AI research — all data-science-heavy domains that pay at or above Amazon rates. Boeing represents the industrial data science opportunity: massive datasets from aircraft sensors, manufacturing quality control, and supply chain analytics. Boeing pays less than consumer tech but offers stability and complex engineering problems. Expedia and Zillow anchor the domain-specific data science market — travel pricing algorithms, dynamic forecasting, and real estate price modeling. These companies pay competitively and offer senior data scientists meaningful ownership of high-impact models.

The result: Seattle has more senior data science positions per capita than almost any US city outside San Francisco, with a particularly deep market for ML-adjacent data science roles.

Data Scientist Salary in Seattle by Experience Level

Median total compensation: ~$162,000/year

A few important notes on these ranges:

Base salary vs total comp: Big Tech companies (Amazon, Microsoft, Meta) pay 30–60% of total compensation in RSUs. The gap between base and total comp widens significantly at senior levels.

Amazon L5 vs L6: At Amazon, L5 data scientists earn $150K–$210K total comp; L6 seniors earn $200K–$290K. The leveling decision at Amazon has a bigger salary impact than at most other employers.

Startups: Seattle data science startups typically offer lower base salaries ($100K–$150K for senior roles) but higher equity percentages. The tradeoff depends heavily on company stage and trajectory.

Top Seattle Employers and What They Pay Data Scientists

Amazon Science / AWS ML

Amazon is the dominant employer for Seattle data scientists. AWS ML — which builds SageMaker, Amazon Comprehend, Amazon Forecast, and related services — runs significant data science teams. Amazon Science focuses on research-oriented roles, often requiring PhD credentials.

L5 (Mid-level): $160,000–$210,000 total comp

L6 (Senior): $200,000–$280,000 total comp

L7 (Staff): $280,000–$400,000+ total comp

Signing bonus: $20,000–$60,000 (front-loaded RSU vesting hedge)

Amazon’s compensation is heavily weighted toward RSUs on a 4-year vest with a back-loaded schedule: 5%-15%-40%-40%. Year 1–2 effective comp is often lower than the headline number.

Microsoft Research / Azure AI

Microsoft pays slightly lower base salaries than Amazon but offers more predictable RSU vesting and a generally less intense work culture.

Senior Data Scientist (Level 63–64): $170,000–$230,000 total comp

Principal Data Scientist (Level 65–66): $220,000–$320,000 total comp

Distinguished Scientist (Level 67+): $350,000–$500,000+ total comp

Microsoft’s Annual Performance Bonus (target 15–20% of base at senior levels) is a meaningful component that Amazon’s structure doesn’t replicate as directly.

Meta Seattle

Meta’s Seattle office focuses primarily on infrastructure, ads, and integrity engineering. Data science roles at Meta sit in the Data Scientist (IC) and Research Scientist (RS) tracks.

IC3–IC4 (Junior-Mid): $150,000–$220,000 total comp

IC5 (Senior): $230,000–$320,000 total comp

IC6 (Staff): $320,000–$450,000+ total comp

Meta’s RSUs vest quarterly after a one-year cliff, creating more predictable income flow than Amazon’s back-loaded schedule.

Google Seattle

Google’s Seattle presence has grown substantially, particularly around Google Cloud and AI research roles.

L4 (Mid-level): $175,000–$240,000 total comp

L5 (Senior): $230,000–$320,000 total comp

L6 (Staff): $320,000–$450,000+ total comp

Boeing Analytics

Boeing offers a very different value proposition: stable employment, defined-benefit pension contributions, and meaningful work on complex real-world systems — at significantly lower pay than tech companies.

Mid-level Data Scientist: $95,000–$130,000 base

Senior Data Scientist: $125,000–$165,000 base

Staff Data Scientist: $155,000–$200,000 base

Boeing rarely pays significant RSUs. The compensation is base-heavy with aerospace industry benefit packages.

Expedia Group

Expedia is one of Seattle’s oldest major data science employers, with deep investment in pricing models, demand forecasting, and customer analytics.

Mid-level: $130,000–$160,000 total comp

Senior: $160,000–$210,000 total comp

Staff: $200,000–$270,000 total comp

Zillow

Zillow’s Zestimate model is one of the most publicly known ML applications in real estate. The Seattle HQ has strong data science teams focused on pricing, market analytics, and mortgage optimization.

Mid-level: $125,000–$155,000 total comp

Senior: $155,000–$200,000 total comp

WA State Tax Advantage

This is the single most underappreciated factor in Seattle compensation. Washington has no state income tax. For a data scientist earning $130,000 base salary, this creates a direct financial advantage over living and working in California:

At $130,000 salary:

Seattle take-home (federal taxes only, approximately): ~$94,500/year

San Francisco take-home (federal + CA 9.3% marginal rate at $130K): ~$83,500/year

Difference: ~$11,000/year — purely from state tax structure

At $155,000 salary (Seattle median):

Seattle net: ~$110,000

San Francisco net: ~$96,000 (CA’s 10.3% bracket)

Difference: ~$14,000/year

At $200,000 salary (senior level):

Seattle net: ~$138,000

San Francisco net: ~$119,000 (CA 12.3% bracket)

Difference: ~$19,000/year

Factoring in lower Seattle rent (median 1-bedroom ~$2,100 vs San Francisco ~$3,100 = $12,000/year difference), a $200K Seattle data scientist takes home approximately $31,000 more per year than the same salary in San Francisco.

This is why many senior data scientists actively choose Seattle over Bay Area offers even when the nominal salary is $20K–$30K lower.

Skills That Command Higher Pay

Seattle’s data science market rewards specific skill profiles more than a generic “data scientist” background:

Machine Learning and Deep Learning — PyTorch and TensorFlow proficiency is table stakes at Amazon and Microsoft. Data scientists who have trained, fine-tuned, and deployed production ML models earn 20–30% premiums over those with primarily analytical or BI backgrounds. Natural Language Processing (NLP) — Particularly in demand post-GPT. Skills in LLM fine-tuning, RAG (retrieval-augmented generation), and conversational AI command significant premiums at Amazon Alexa, Microsoft Copilot teams, and AI startups throughout the ecosystem. SQL and Data Engineering Fluency — Data scientists who can write efficient complex SQL, understand query optimization, and work comfortably with distributed data warehouses (Redshift, Snowflake, BigQuery) save teams from needing separate data engineering support, which translates to higher perceived value. Apache Spark and Distributed Computing — Essential for working with Amazon- and Microsoft-scale datasets. PySpark fluency is a differentiator for senior roles that require working with petabyte-scale data. AWS SageMaker — Given Amazon’s dominance, SageMaker expertise is the closest thing to a “local currency” for Seattle data scientists. Data scientists who can build end-to-end ML pipelines on SageMaker are in perpetual demand. Causal Inference and Experimentation — A/B testing at scale is fundamental to Amazon (pricing, rankings), Microsoft (product telemetry), and Expedia (booking conversion). Data scientists with strong causal inference backgrounds command senior-level compensation even with fewer years of experience.

Seattle vs Bay Area Data Science Salaries

The Bay Area still pays higher absolute base salaries for data scientists, but the gap is smaller than most people assume — and often disappears entirely when accounting for taxes and cost of living.

Where SF wins: Pure salary ceiling. The top 5% of data science roles (staff scientists, research scientists at FAANG) pay more in SF than anywhere in Seattle. Where Seattle wins: Everything between $100K and $300K total compensation. The mid-to-senior data scientist gets a better financial outcome in Seattle almost every time when tax and rent differences are factored in.

For a comparison across international markets, see data scientist salary in Berlin — a popular alternative for data scientists who want European work-life balance without sacrificing technical challenge.

Also see the data scientist salary guide for 2026 for a multi-city perspective.

How to Negotiate Your Data Science Offer in Seattle

Seattle’s Big Tech market creates specific negotiation dynamics that differ from startup-heavy markets:

Know your level before the offer. Amazon, Microsoft, and Meta level data scientists on internal rubrics that dramatically affect compensation. If you receive an offer, ask what level they’re placing you at — and whether they’ve considered the next level. Moving from L5 to L6 at Amazon is worth $50K–$100K in total comp. Push for the level conversation before total comp discussion. Use competing offers. Seattle’s density of Big Tech employers makes competing offers more accessible than in other markets. An offer from Amazon is the most effective tool for negotiating at Microsoft, and vice versa. Data scientists with 5+ years of experience who work the market typically receive 2–3 offers within 60 days of searching actively. Negotiate RSU grants, not just base. Base salary at Big Tech companies is relatively compressed (Amazon famously caps base at $350K). The real negotiation leverage is in RSU grant size and signing bonus (which front-loads compensation for Amazon’s back-weighted vest schedule). Ask specifically: “What flexibility is there on the initial RSU grant?” Address the Amazon back-load directly. Amazon’s RSU vesting (5%/15%/40%/40%) means year 1–2 compensation is lower than the headline. A common negotiation tactic: request an increased signing bonus in lieu of RSU increases, since signing bonuses are not subject to the same vesting schedule constraints. Benchmark against market data. Before any negotiation conversation, use CareerCheck’s Seattle data scientist salary data to understand current market ranges at your experience level. Coming into a negotiation without market benchmarks consistently leaves money on the table. Consider total comp across 4 years. Because RSU vesting timelines differ (Amazon’s back-load vs Meta’s quarterly vest vs Microsoft’s more standard schedule), always model total comp over 4 years when comparing offers, not just year-1 numbers.

Adjacent Roles Worth Considering

If you’re evaluating Seattle data science opportunities, these adjacent roles are also in strong demand:

ML Engineer salaries in Seattle: $175K–$300K total comp — for data scientists who skew toward production deployment and ML infrastructure

Software Engineer salaries in Seattle: $165K–$285K total comp — the broader engineering market context

Is Seattle the Right Market in 2026?

For most data scientists with 3+ years of experience, Seattle represents the best combination of absolute salary, tax-adjusted take-home, career growth opportunities, and quality of life available in the US tech market.

The drawbacks are real: the weather (gray and rainy October–April), the commute culture if you land at Amazon or Microsoft, and a cost of living that has risen significantly over the last decade. But the financial mathematics — no state income tax, strong base salaries, meaningful RSU programs at multiple employers — favor Seattle in ways that compound over a career.

For mid-senior data scientists (3–8 years experience), Seattle’s combination of Amazon, Microsoft, and Meta opportunities means you’re rarely more than a few weeks away from an offer at a company that will materially change your financial trajectory.

Use CareerCheck’s Seattle data scientist salary tool to benchmark your current compensation against live market data — and find out whether it’s time to negotiate, move, or make your next career move.