Mid-Level or Senior Engineering Data Scientist

Boeing•Everett, WA

3d•$137,700 - $234,600•Onsite

About The Position

The Boeing Company is seeking a Mid-Level (Level 3) or Senior (Level 4) Engineering Data Scientist to join our Aerospace Safety Analytics team, supporting the Chief Aerospace Safety Office (CASO). This team collaborates cross-functionally to leverage data for actionable safety insights, driving risk-based decisions for internal and external stakeholders. The role involves improving aircraft safety by deriving and delivering impactful data-driven insights. The selected candidate will lead and execute analytic activities, including conducting analyses and building data-driven tools to monitor, assess, and predict safety risks in aircraft design and operation. This includes utilizing aviation data for descriptive and predictive analyses, model development and validation, data visualization, reporting, and communicating insights and recommendations.

Requirements

Bachelor of Science degree in Engineering, Engineering Technology (including Manufacturing Technology), Computer Science, Data Science, Mathematics, Physics, Chemistry or non-US equivalent qualifications directly related to the work statement.
Level 3: 5+ years of related work experience or an equivalent combination of education and experience.
Level 4: 9+ years of related work experience or an equivalent combination of education and experience.
Excellent written/verbal communication skills.
Experience leading or managing projects that involved cross-functional or cross-business unit teams.
4+ years of experience in programming languages such as JavaScript, C#, Python, SQL, etc.
Experience developing the visual design, branding and data visualizations to produce modern, compelling products.
4+ years of experience designing and creating new algorithms for the analysis of data to address project requirements, evaluate performance of data analysis algorithms and select and apply algorithms to meet application requirements.
Must meet U.S. export control compliance requirements. A “U.S. Person” as defined by 22 C.F.R. §120.62 is required. “U.S. Person” includes U.S. Citizen, U.S. National, lawful permanent resident, refugee, or asylee.

Nice To Haves

Experience in aviation or aviation related activities.
Experience in applying statistical concepts.
Experience in designing and implementing Natural Language Processing (NLP) models using machine learning techniques including neural networks, deep learning and transformer architectures.
Experience with Agile and Scalable Agile methodologies.
Experience applying machine learning or data mining techniques to sensor or temporal data.

Responsibilities

Design, develop, validate, and maintain descriptive, diagnostic, predictive, and prescriptive models that quantify risk, identify anomalies, and support safety strategy.
Perform exploratory, statistical, and time/trajectory-based analyses to surface safety trends, root causes, and risk drivers.
Build reusable data products, APIs, dashboards, and monitoring systems that operationalize analytic insights for engineering, flight operations, and safety teams.
Translate analytic results into clear findings, technical reports, and actionable recommendations for cross-functional stakeholders.
Ingest, clean, fuse, and validate large and diverse aviation datasets (ADS-B, FDM, flight alerts, text reports, etc.) and build robust ETL/ELT pipelines.
Drive best practices for reproducible analysis, model governance, documentation, and first-time quality.