Research Scientist Jobs in Seattle, WA
Research Scientist jobs in Seattle concentrate in biotech, life sciences, technology, and environmental research, with major clusters in South Lake Union, the University District, and Eastside corridors in Bellevue and Redmond. Employers hiring right now include ByteDance, TikTok, and Apple. See the openings below and apply to the ones that match your experience.
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Showing 5 of 63+ Research Scientist jobs
DESCRIPTION
In this role, you’ll work across a variety of research methodologies to optimize our data collection, create scalable analytical approaches, and deep dive the Seller experience to create rigorous, quantitative insights that senior leaders use to set strategy.
Key job responsibilities
Key Job Responsibilities
- Apply psychometric and survey methodology techniques (e.g., IRT, factor analysis, scale development, single-item indicators) to measure seller experience constructs with scientific rigor
- Design and implement frameworks that link seller attitudinal data to behavioral outcomes and identify high-impact opportunity areas
- Design and execute statistical analyses including regression modeling, significance testing, and driver analysis to identify what matters most to sellers
- Apply observational causal evaluation methods to estimate the effects of policy changes, product launches, and platform interventions on seller experience
- Design, build and maintain analytical pipelines that transform raw survey data into production-ready metrics, reports, and dashboards
- Design and build systems to analyze open-ended survey responses using text classification, thematic coding, and natural language processing techniques
- Design and monitor processes improve survey response rates, sampling methodology, and data quality
- Productionalize research code: take analyses from prototype to automated, reproducible pipelines that run reliably in production environments
- Communicate findings clearly to technical and non-technical audiences through written reports, data visualizations, and presentations
- Collaborate and influence with cross-functional partners to translate business questions into well-defined research problems and scientific metrics
- Document research methods, assumptions, and limitations transparently to ensure reproducibility
A day in the life
Your day typically starts with the data. You might spend the morning reviewing satisfaction trends, investigating a shift in a key metric, and pulling together an analysis that explains what's driving it. You'll regularly meet with external teams to help them understand how a proposed product will affect seller sentiment and what the data says they should prioritize. You'll also spend time in R or Python building, training, or testing models to improve how we measure and act on sentiment data.
About the team
Our team owns the research and measurement infrastructure that tracks satisfaction across all 2.1 million selling partners on Amazon, spanning Seller Central, Next Gen Selling, and Mobile. We sit at the intersection of data and strategy, partnering with teams across product, design, and engineering to advocate for seller experience improvements. This is a high-visibility team where the work is consequential, the stakeholders are senior, and the problems are genuinely hard.
BASIC QUALIFICATIONS
- PhD, or Master's degree and 5+ years of quantitative field research experience
- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
- Experience analyzing both experimental and observational data sets
- Experience programming, prototyping and scripting with Oracle, SQL, Hive, Pig, SAS, R, Weka, or Python
- Knowledge of R, MATLAB, Python or similar scripting language
- Experience with lab-based user testing, remote testing, iterative prototype testing, survey design, and usage of multiple methods within a study
- Experience applying basic statistical methods (e.g. regression) to difficult business problems
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience in solving complex business challenges by delivering accurate and timely financial models, analysis, and recommendations that have a proven impact on business (e.g., financial savings, operational improvements, or customer benefits), or experience working with Excel and large-scale data mining and reporting tools such as Python, SQL, or Tableau
- Experience with survey research methodology and psychometric measurement (e.g., item response theory, factor analysis, scale construction, reliability analysis) as well as single-item indicators
PREFERRED QUALIFICATIONS
- Experience with agile development
- Experience in causal modeling like graphical models, causal Bayesian network, potential outcomes, A/B testing, experiments, quasi-experiments, and data science workflows
- Experience with any programming language such as Python, Java, C++
- Knowledge of machine learning processing: computer vision, NLU, NLP or operations research
- Experience with AWS services including S3, Redshift, EMR and RDS
- Experience with various types of research methodologies is key, including quant, qual, 1P & 3P data, trend analysis & forecasting, etc.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually
DESCRIPTION
In this role, you’ll work across a variety of research methodologies to optimize our data collection, create scalable analytical approaches, and deep dive the Seller experience to create rigorous, quantitative insights that senior leaders use to set strategy.
Key job responsibilities
Key Job Responsibilities
- Apply psychometric and survey methodology techniques (e.g., IRT, factor analysis, scale development, single-item indicators) to measure seller experience constructs with scientific rigor
- Design and implement frameworks that link seller attitudinal data to behavioral outcomes and identify high-impact opportunity areas
- Design and execute statistical analyses including regression modeling, significance testing, and driver analysis to identify what matters most to sellers
- Apply observational causal evaluation methods to estimate the effects of policy changes, product launches, and platform interventions on seller experience
- Design, build and maintain analytical pipelines that transform raw survey data into production-ready metrics, reports, and dashboards
- Design and build systems to analyze open-ended survey responses using text classification, thematic coding, and natural language processing techniques
- Design and monitor processes improve survey response rates, sampling methodology, and data quality
- Productionalize research code: take analyses from prototype to automated, reproducible pipelines that run reliably in production environments
- Communicate findings clearly to technical and non-technical audiences through written reports, data visualizations, and presentations
- Collaborate and influence with cross-functional partners to translate business questions into well-defined research problems and scientific metrics
- Document research methods, assumptions, and limitations transparently to ensure reproducibility
A day in the life
Your day typically starts with the data. You might spend the morning reviewing satisfaction trends, investigating a shift in a key metric, and pulling together an analysis that explains what's driving it. You'll regularly meet with external teams to help them understand how a proposed product will affect seller sentiment and what the data says they should prioritize. You'll also spend time in R or Python building, training, or testing models to improve how we measure and act on sentiment data.
About the team
Our team owns the research and measurement infrastructure that tracks satisfaction across all 2.1 million selling partners on Amazon, spanning Seller Central, Next Gen Selling, and Mobile. We sit at the intersection of data and strategy, partnering with teams across product, design, and engineering to advocate for seller experience improvements. This is a high-visibility team where the work is consequential, the stakeholders are senior, and the problems are genuinely hard.
BASIC QUALIFICATIONS
- PhD, or Master's degree and 5+ years of quantitative field research experience
- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
- Experience analyzing both experimental and observational data sets
- Experience programming, prototyping and scripting with Oracle, SQL, Hive, Pig, SAS, R, Weka, or Python
- Knowledge of R, MATLAB, Python or similar scripting language
- Experience with lab-based user testing, remote testing, iterative prototype testing, survey design, and usage of multiple methods within a study
- Experience applying basic statistical methods (e.g. regression) to difficult business problems
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience in solving complex business challenges by delivering accurate and timely financial models, analysis, and recommendations that have a proven impact on business (e.g., financial savings, operational improvements, or customer benefits), or experience working with Excel and large-scale data mining and reporting tools such as Python, SQL, or Tableau
- Experience with survey research methodology and psychometric measurement (e.g., item response theory, factor analysis, scale construction, reliability analysis) as well as single-item indicators
PREFERRED QUALIFICATIONS
- Experience with agile development
- Experience in causal modeling like graphical models, causal Bayesian network, potential outcomes, A/B testing, experiments, quasi-experiments, and data science workflows
- Experience with any programming language such as Python, Java, C++
- Knowledge of machine learning processing: computer vision, NLU, NLP or operations research
- Experience with AWS services including S3, Redshift, EMR and RDS
- Experience with various types of research methodologies is key, including quant, qual, 1P & 3P data, trend analysis & forecasting, etc.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually
See All 63 Research Scientist Jobs in Seattle
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Find Research Scientist JobsResearch Scientist Job Market in Seattle
Who's Hiring
- ByteDance14
- TikTok13
- Apple8
- Amazon8
- NVIDIA6
Top Industries Hiring
- Technology & Software18
- Electronics & Hardware7
- Science & Research6
- Retail4
- E-Commerce & Online Marketplaces4
Research Scientist Jobs in Seattle: Frequently Asked Questions
How do I get a research scientist job in Seattle?
Focus your search on Seattle's three deepest hiring pools: biotech and life sciences firms concentrated in South Lake Union, technology companies building out AI and computational research teams in the University District and Eastside, and environmental or oceanographic institutions near the waterfront. Candidates who combine domain expertise with experience in wet-lab techniques, data analysis, or published research tend to move faster through hiring here than generalists.
Which companies hire research scientists in Seattle?
Employers hiring research scientists in Seattle right now include ByteDance, TikTok, and Apple, based on current listings on Migrate Mate as of August 2026. Seattle's mix of global technology companies, mid-size biotech firms, and federally funded research institutions means openings exist at a wide range of organizational scales.
Are there remote research scientist jobs in Seattle?
Yes, though availability depends heavily on the type of work: computational, bioinformatics, and data-focused roles are far more remote-friendly than bench or wet-lab positions, which require on-site presence. About 23% of research scientist openings tied to Seattle are remote or hybrid as of August 2026, with the majority of those concentrated in software-adjacent and analytical research functions. Hybrid schedules with two to three days on-site are common among Seattle's larger biotech and tech employers.
How can I get a research scientist job in Seattle with little or no experience?
The most realistic entry path in Seattle is a research associate or junior scientist role at one of the city's many mid-size biotech or diagnostics companies, which tend to hire more entry-level candidates than large pharmaceutical employers. University of Washington research labs and institutes like the Fred Hutchinson Cancer Center regularly bring on research technicians and coordinators who can build credentials on the job. Familiarity with Python, R, or standard lab automation tools gives candidates a concrete edge over peers with equivalent academic backgrounds.
Which industries hire the most research scientists in Seattle?
Most research scientist openings in Seattle sit in Technology & Software, Electronics & Hardware, and Science & Research, per current listings on Migrate Mate as of August 2026. Seattle's position as a hub for cloud computing, genomics, and environmental science means these sectors sustain consistent demand rather than hiring in isolated waves.
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See All 63 Research Scientist Jobs in Seattle
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