Data Science Lead Jobs in Seattle, WA
Data Science Lead jobs in Seattle, Washington are heavily concentrated in South Lake Union, the Capitol Hill tech corridor, and Bellevue's Eastside cluster, across cloud computing, e-commerce, and healthcare analytics. Employers hiring right now include Amazon, Seattle Public Schools, and Amazon Web Services. See the openings below and apply to the ones that match your experience.
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Showing 5 of 98+ Data Science Lead jobs
DESCRIPTION
This role owns the development and deployment of mathematical optimization models for pick planning, inventory placement, and warehouse layout design. You will formulate ambiguous business problems as concrete scientific models, develop and deploy production-grade solutions, and work closely with engineering partners, product owners, and business stakeholders to deliver measurable impact.
Because UTR operations are complex and inter-connected (e.g., inbound stow vs. outbound pick), this role requires a strong understanding of these relationships and the ability to make trade-offs at the system level. You will interface directly with non-technical product owners and business leaders, manage expectations, and take an active part in influencing the feature roadmap.
Key job responsibilities
- Design, develop, and deploy mathematical optimization models (e.g., Mixed Integer Programming, meta-heuristics) to improve outbound picking efficiency, including pick planning and inventory placement.
- Build simulation models to evaluate warehouse layout designs, test optimization solutions offline, and answer strategic what-if questions.
- Formulate complex, ambiguous business problems into well-defined scientific solutions with clear objectives and constraints.
- Collaborate with engineering teams to productionize models, establish data pipelines, and create scalable architectures.
- Track solution performance post-deployment, identify issues through deep dives, and iteratively improve model quality.
- Communicate technical concepts clearly to diverse stakeholders — scientists, engineers, product managers, and business leaders — through documentation, presentations, and design reviews.
- Author peer-reviewed research papers on developed models and contribute to the internal scientific community.
BASIC QUALIFICATIONS
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- 3+ years of building models for business application experience
- Knowledge of programming languages such as C/C++, Python, Java or Perl
- Knowledge of agile development and best coding practices including peer code reviews, and unit testing
- Experience deploying machine learning or optimization models into production systems.
PREFERRED QUALIFICATIONS
- Experience in program management, logistics, operations, supply chain, transportation, or a related field
- Experience with AWS Services including EC2, Lambda, S3, DynamoDB, SQS
- Experience communicating technical concepts to non-technical audiences
- Familiarity with simulation-based optimization and discrete-event simulation
- Experience with causal inference, econometrics, or machine learning (e.g., neural networks, reinforcement learning)
- Track record of publishing research at peer-reviewed conferences or journals
- Demonstrated ability to work semi-autonomously, gathering business requirements and translating them into scientific solutions
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 - 142,800.00 - 193,200.00 USD annually
DESCRIPTION
This role owns the development and deployment of mathematical optimization models for pick planning, inventory placement, and warehouse layout design. You will formulate ambiguous business problems as concrete scientific models, develop and deploy production-grade solutions, and work closely with engineering partners, product owners, and business stakeholders to deliver measurable impact.
Because UTR operations are complex and inter-connected (e.g., inbound stow vs. outbound pick), this role requires a strong understanding of these relationships and the ability to make trade-offs at the system level. You will interface directly with non-technical product owners and business leaders, manage expectations, and take an active part in influencing the feature roadmap.
Key job responsibilities
- Design, develop, and deploy mathematical optimization models (e.g., Mixed Integer Programming, meta-heuristics) to improve outbound picking efficiency, including pick planning and inventory placement.
- Build simulation models to evaluate warehouse layout designs, test optimization solutions offline, and answer strategic what-if questions.
- Formulate complex, ambiguous business problems into well-defined scientific solutions with clear objectives and constraints.
- Collaborate with engineering teams to productionize models, establish data pipelines, and create scalable architectures.
- Track solution performance post-deployment, identify issues through deep dives, and iteratively improve model quality.
- Communicate technical concepts clearly to diverse stakeholders — scientists, engineers, product managers, and business leaders — through documentation, presentations, and design reviews.
- Author peer-reviewed research papers on developed models and contribute to the internal scientific community.
BASIC QUALIFICATIONS
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- 3+ years of building models for business application experience
- Knowledge of programming languages such as C/C++, Python, Java or Perl
- Knowledge of agile development and best coding practices including peer code reviews, and unit testing
- Experience deploying machine learning or optimization models into production systems.
PREFERRED QUALIFICATIONS
- Experience in program management, logistics, operations, supply chain, transportation, or a related field
- Experience with AWS Services including EC2, Lambda, S3, DynamoDB, SQS
- Experience communicating technical concepts to non-technical audiences
- Familiarity with simulation-based optimization and discrete-event simulation
- Experience with causal inference, econometrics, or machine learning (e.g., neural networks, reinforcement learning)
- Track record of publishing research at peer-reviewed conferences or journals
- Demonstrated ability to work semi-autonomously, gathering business requirements and translating them into scientific solutions
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 - 142,800.00 - 193,200.00 USD annually
See All 98 Data Science Lead Jobs in Seattle
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Find Data Science Lead JobsData Science Lead Job Market in Seattle
Who's Hiring
- Amazon53
- Seattle Public Schools5
- Amazon Web Services4
- Truveta3
- University Of Washington3
Top Industries Hiring
- Technology & Software36
- Retail32
- E-Commerce & Online Marketplaces31
- Biotechnology & Pharmaceuticals8
- Healthcare & Medical Services3
Data Science Lead Jobs in Seattle: Frequently Asked Questions
How do I get a data science lead job in Seattle?
Focus your search on South Lake Union and the Eastside, where cloud platforms, e-commerce, and biotech firms concentrate the most data science lead openings. Candidates who demonstrate experience leading cross-functional teams, building ML pipelines at scale, and translating model outputs into business decisions stand out here. Familiarity with cloud-native environments and a portfolio of shipped, production-grade work gives you a meaningful edge in Seattle's competitive market.
Which companies hire data science leads in Seattle?
Employers hiring data science leads in Seattle right now include Amazon, Seattle Public Schools, and Amazon Web Services, based on current listings on Migrate Mate as of July 2026. Seattle's hiring mix leans toward large tech platforms, health systems, and high-growth startups that embed data science leads inside product and engineering teams.
Are there remote data science lead jobs in Seattle?
Yes, though availability varies: data science lead roles that center on modeling, analysis, and strategy tend to be remote-friendly, while those requiring close collaboration with on-site engineering teams are more likely hybrid. About 61% of data science lead openings tied to Seattle are remote or hybrid as of July 2026, reflecting the city's broad adoption of flexible work across tech and healthcare. Purely remote roles are most common at Seattle's larger cloud and software employers.
How can I get a data science lead job in Seattle with little or no experience?
The most realistic entry path in Seattle is moving into a lead role from a senior individual-contributor position at one of the city's mid-size tech or healthtech companies, which often promote internally before hiring externally. Amazon, Zillow, and similar Seattle-headquartered firms run associate data science programs that build toward lead tracks. Developing mentorship experience, contributing to open-source ML projects, and building visibility in Seattle's local data science meetup community all strengthen a promotion case.
Which industries hire the most data science leads in Seattle?
Seattle data science lead roles concentrate in Technology & Software, Retail, and E-Commerce & Online Marketplaces, based on current listings on Migrate Mate as of July 2026. Seattle's position as a hub for cloud infrastructure, enterprise software, and major health systems makes these sectors the primary drivers of local demand for data science leadership.
Related Jobs in Washington
See All 98 Data Science Lead Jobs in Seattle
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