Senior Data Scientist
About The Position
The Boeing Company is currently seeking a Senior Data Scientist to join the Boeing Test & Evaluation (BT&E) Business Operations team in Berkeley, MO or Seattle, WA. The candidate will lead cross-functional teams to define, build, validate, and deploy advanced predictive and prescriptive analytics solutions that drive measurable business outcomes. This senior individual contributor / technical leader will evaluate business objectives, translate stakeholder needs into analytic requirements, choose appropriate methods and algorithms, perform data preparation and feature engineering, and operationalize models into production systems. The role requires strong domain/business acumen, excellent communication and leadership skills, hands-on modeling experience, and proven success deploying production-grade analytics.
Requirements
- Ability to obtain a US Security Clearance for which the US Government requires US Citizenship
- Bachelor’s degree or higher
- 5+ years of experience with AI/ML technologies, frameworks, models and ensembles
- 5+ years with container and container orchestration (Docker and Kubernetes)
- 5+ years of experience with data engineering and data pipelines for On-Prem cloud, hybrid data models and data warehouses
- 5+ years of experience with software programming/scripting (such as Python, Unix/Linux type batch scripting, FORTRAN, C / C++)
Nice To Haves
- 5+ years of experience in the manufacturing or aviation domain
- 5+ years of experience with big data technologies and data engineering practices
- Experience in multi-cloud and hybrid AI architecture
- Experience with generative AI, NLP, computer vision, or reinforcement learning
- Experience with CI/CD pipelines, DevOps practices and containerized deployments
- Experience with open-source ML projects or publications in relevant fields
Responsibilities
- Define the strategy to build highly reliable and scalable ML and AI solutions that align with the organization’s business goals and objectives
- Lead the creation and implementation of scalable, robust, and high-performance ML architectures including MLOps, AIOps leveraging cloud native services (AWS, Azure, GCP) and open-source frameworks
- Design, build, and optimize machine learning models, ensuring accuracy, efficiency, and scalability
- Partner with product managers, engineers, and business stakeholders to define problem statements, success metrics, and deployment requirements
- Collaborate with data engineers, data architect, software developers, and DevOps teams to integrate ML models into production systems
- Assess and recommend ML tools, frameworks, and platforms to deliver business value and foster innovation
- Monitor and optimize ML models and systems for latency, throughput, and cost-efficiency in production
- Ensure ML systems adhere to ethical guidelines, data privacy regulations, and industry standards
- Design and development of Generative AI and AI use cases (LLMs, RAG, Agentic, multi model AI, fine tuning. Vector databases and prompt engineering)
- Lead organizational change for the adoption of new platforms, machine learning tools and analytics workflows
- Own all communication and collaboration channels pertaining to strategy and assigned projects, including regular stakeholder, senior leadership, and cross-team updates
Benefits
- health insurance
- flexible spending accounts
- health savings accounts
- retirement savings plans
- life and disability insurance programs
- paid and unpaid time away from work
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Number of Employees
5,001-10,000 employees
