Data Scientist (data Science)

Boeing Boeing · Aerospace · Everett, WA

Boeing Commercial Airplanes is seeking a Senior Data Scientist to join the Supply Chain Functional Excellence organization. The role involves developing and building AI/ML products and services, deploying models into business workflows, and providing data-driven insights to aid leadership decision-making. The position requires strong technical skills in Python/R, SQL, ML algorithms, and data visualization tools, with a focus on translating complex models into tangible business outcomes. Experience with Knowledge Graphs and MLOps is preferred.

What you'd actually do

  1. Develop and build Artificial Intelligence (AI) and Machine Learning (ML) products and services.
  2. Work effectively with cross-functional teams to generate, test, and deploy models into existing business workflows, solutions, and tools to accelerate the business forward.
  3. Contribute as a team member alongside the Business Intelligence (BI) Analysts, Data Scientists, System & Process specialists and work closely with stakeholders to deliver solutions that help The Boeing Company deliver safer, better, and more efficient airplanes and products.
  4. Provide real-time insights for complex business problems and aids senior/executive leadership in their decision-making process.

Skills

Required

  • Python or R
  • advanced SQL
  • machine learning algorithms (supervised/unsupervised)
  • statistical modeling
  • data cleaning/preprocessing techniques
  • Tableau, Power BI, Matplotlib, DataIku
  • Knowledge Graphs like Neo4j/ArangoDB
  • Ontologies from Datasets
  • integrating APIs into ETL pipelines

Nice to have

  • Knowledge Graphs | Experience designing and building knowledge graphs in Neo4j/ArangoDB or similar technology (data modeling, entity resolution, relationship traversal/querying). GraphRAG/LLM experience is a plus.
  • Supply Chain Expertise | Specific domain knowledge in Supply Chain systems and processes.
  • Master’s degree or PhD in a quantitative field.
  • Cloud Platforms | Experience with cloud environments (AWS, GCP, or Azure).
  • MLOps and Deployment | Experience in moving models into production, containerization (Docker, Kubernetes), and building automated pipelines.
  • Data & AI Platforms | Experience with Databricks, Dataiku (or similar) to build, deploy, and operationalize data pipelines and AI/ML workflows.
  • Leadership | Proven experience in mentoring junior data scientists and leading projects from end-to-end.

What the JD emphasized

  • technically competent
  • strong communication skills
  • translate opaque model outputs to tangible real-world business outcomes

Other signals

  • develop and build AI/ML products and services
  • deploy models into existing business workflows
  • data-driven transformation
  • provide real-time insights for complex business problems
  • aid senior/executive leadership in their decision-making process