Boeing

Full Stack Data Scientist

Boeing
US Seattle, WA, US
Hybrid 2026-07-03
Announced salary
$137,700 - $186,300
Low
$101K
Median
$133K
High
$176K
Market in Seattle · BLS OEWS 2025
Estimated net pay
$8,782 - $11,559
/month · 23% withheld
after tax & contributions · Single, no dependents

Job description

At Boeing, we innovate and collaborate to make the world a better place. We’re committed to fostering an environment for every teammate that’s welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us. At Boeing, we innovate and collaborate to make the world better. Boeing Defense, Space \& Security (BDS) is seeking a Full Stack Data Scientist to join the Business Transformation organization in support of modernizing how BDS operates through artificial intelligence, machine learning, and advanced digital capabilities. This role will help build and scale the technical foundations that enable secure, reliable, and production\-ready AI/ML solutions across the enterprise. This position is ideal for a data scientist who brings a blend of data science, data engineering, MLOps, platform engineering, DevOps, and site reliability engineering (SRE) experience. The selected candidate will help design, implement, secure, and operate the infrastructure and platform services that support data pipelines, model training, model deployment, observability, and AI application delivery. The role will work across on\-premises, hybrid, and cloud\-based environments, with a strong emphasis on enterprise\-grade security, resiliency, traceability, and operational excellence. The full stack data scientist in this role will partner closely with data scientists, software engineers, data engineers, cybersecurity teams, infrastructure teams, and business stakeholders to accelerate adoption of AI/ML capabilities within BDS. This includes enabling both traditional machine learning workflows and emerging generative AI use cases, including support for on\-premises model serving, retrieval\-augmented generation architectures, and modern model lifecycle management practices. The role requires strong systems thinking and the ability to translate business and mission needs into scalable platform solutions. The successful candidate will be expect

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