Lead Artificial Intelligence/Machine Learning Data Scientist

Boeing

Lead AI/Machine Learning Data Scientist at Boeing driving innovative AI and ML solutions. Collaborate with teams to deploy cutting-edge data science applications across multiple domains.

Posted 6/10/2026full-timeSeattle • Texas, Washington • 🇺🇸 United StatesSenior💰 $218,450 - $295,550 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformJavaPythonScalaSQL

About the role

Key responsibilities & impact

Evaluate business objectives, collaborate in user research, understand process nuances, determine stakeholder needs, and identify requirements
Champion the AI cause with stakeholder groups, educate and excite sponsors about possibilities offered by the data science discipline
Choose best fit methods, define algorithms, validate, and deploy models to achieve business results
Build AI solutions iteratively, in short cycles to enable a fail-fast, rapid learning environment
Perform necessary data preparation and enhancements to models
Interface directly with senior business leaders and stakeholders to architect and lead the development of advanced analytics solutions supporting Aircraft operations, Engineering, Supply Chain, Manufacturing, Quality, and Safety
Work with data scientists leads across domains to ensure functional excellence in this technical field and will provide mentoring, technical leadership, and training to the data scientist community to accelerate and develop the talent base
Provide thought leadership for machine learning and advanced analytics methods at Boeing and externally
Engage with stakeholders across the business to identify applications across the enterprise, beyond the initial use case, and lead the implementation of these applications to capture business value
Evaluate technologies, assist in identifying capability gaps, develop and teach best practices and technology standards, and work alongside the rest of the global data scientists and technical leads in Analytics organization
Ensure analytics solutions meet the business requirements and are implemented in a timely manner to validate business value
Work effectively with cross-functional teams in the analysis of highly complex data sets using advanced analytics techniques such as machine learning, advanced statistical analysis, visual analysis, text analysis, mathematical optimization, and simulation
Identify modeling attributes and parameters
Follow best practices and standard processes for model validation and refinement as per business requirements
Assess performance of models and analysis and confirm that business objectives were met
Work with business unit stakeholders to develop and sustain analytics solutions

Requirements

What you’ll need

10+ years of experience working with projects, teams, and/or leaders in the analytics and data science space
10+ years of experience with various machine learning methods such as regression, clustering, classification, decision trees, natural language processing, ensemble methods, support vector machines (SVM), deep learning, reinforcement learning, etc.
5+ years of experience in designing and implementing Natural Language Processing (NLP) models using machine learning techniques including neural networks, deep learning and transformer architectures
5+ years of experience researching and applying large language and generative AI models
Master’s degree in data science or equivalent (preferred)
Experience developing and implementing end-to-end Agentic AI solutions (preferred)
Experience in supply chain domain (preferred)
Experience in agile and product-oriented development (preferred)
Experience in building ML models and bringing them to full production use within the industry (preferred)
Experience training machine learning models in a cloud computing environment such as: Amazon Web Services, Google Cloud Platform, Microsoft Azure (preferred)
Experience programming in one or more of the following: C, C++, Java, Python, Scala (preferred)
Experience with statistical software and database languages (e.g., SQL) (preferred)
Experience in advanced statistics (e.g., probability theory and distributions, descriptive statistics, matrix algebra, multivariate statistics, polynomial analysis, parametric and non-parametric methods, etc.) (preferred)

Benefits

Comp & perks

Health insurance
Flexible spending accounts
Health savings accounts
Retirement savings plans
Life and disability insurance programs
Paid time away from work

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningnatural language processingdeep learningreinforcement learningregressionclusteringclassificationdecision treessupport vector machinesagentic AI solutions

Soft Skills

collaborationstakeholder engagementmentoringtechnical leadershipthought leadershipcommunicationproblem-solvingcross-functional teamworktrainingbusiness analysis

Certifications

Master’s degree in data science