Seattle, Washington; United States; Virtual
Job ID JR2025464838 Category Data Science & Analytics Role Type Virtual Post Date Jul. 30, 2025

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.
The Boeing Company has an exciting opportunity for an Experienced or Senior Data Scientist - Corporate Audit Leadership Development Program to support Corporate Audit’s Strategic Business Hubs virtually.
Our Strategic Business Hubs are located across the United States in: Renton, WA; Seattle, WA; Everett, WA; Berkeley, MO; Hazelwood, MO; Ridley Park, PA; North Charleston, SC; Mesa, AZ; and Plano, TX.
Are you ready to embark on an exciting career journey with one of the world’s leading aerospace companies?
As an Experienced or Senior Data Scientist, you will be a member of Boeing’s Corporate Audit Data Analytics Team, a national team covering a wide range and scope of audit activities. As a Mid-Level Data Scientist, you will assist Corporate Audit in accomplishing its objectives by bringing a systematic and disciplined approach to evaluate and improve the effectiveness of Boeing’s governance, risk management and internal control environment by providing data and automation support to perform independent evaluations of the adequacy and effectiveness of Boeing’s production, finance, operations, compliance and technology functions.

BASIC QUALIFICATIONS (REQUIRED SKILLS/EXPERIENCE):

• Bachelor’s Degree in Data Science, Computer Science, Statistics, Engineering, or a related field from an accredited institution
• 3+ years of experience leading projects with engineers and data professionals, focusing on innovation, quality management, and analytics in natural language processing and machine learning on unstructured data
• Demonstrated problem-solving and communication skills, with the ability to explain complex technical concepts to business stakeholders
• Proven technical understanding of data preparation methods and machine learning algorithms; experienced in the complete data science process from discovery and cleaning to model selection, validation, and deployment
• Experience in developing tools using LLMs, with skills in restructuring, refactoring, and optimizing code for efficiency

PREFERRED QUALIFICATIONS (DESIRED SKILLS/EXPERIENCE):

• 5+ years of related work experience or an equivalent combination of education and experience
• Master’s Degree from an accredited college/university in Data Science, Computer Science, Statistics, Engineering, or related fields
• In-depth knowledge of AWS resources, configuration, deployment, and architecture
• Ability to utilize a diverse array of technologies and tools as needed to deliver insights, such as fluency in Python; Experience with command-line scripting, data structures, and algorithms; Ability to write production level code
• Demonstrated experience in developing data-driven organizational risk assessments by identifying relevant data, scoring risks based on likelihood and impact, and compiling comprehensive assessment reports to inform decision-making and risk mitigation strategies
• Experience working in a role that develops Data Science solutions as part of a cross-functional team that includes Data Engineers, Product Owners, and Business Intelligence Analysts
• Experience working in highly regulated environments (e.g., aerospace, defense, financial services)

EDUCATION

Bachelor’s Degree or Equivalent Required

• Evaluate advanced business analytics problems into technical approaches that yield actionable recommendations and identify trends, patterns, and insights for data-driven decision making
• Design anomaly detection models and continuous monitoring solutions
• Choose best fit methods, define algorithms, validate, and deploy models to achieve business results
• Perform exploratory data analysis, generate and test working hypotheses, and uncover meaningful trends and relationships
• Create production quality Machine Learning (ML)/Artificial Intelligence (AI) models that can be deployed at scale. Make use of Amazon Web Services (AWS) technologies in solution development, recommend and develop new capabilities
• Communicate technical details of solutions, including mathematical formulations, alternatives, and impact on modeling approach to business stakeholders
• Support the identification, development, and automation of risk assessment metrics to support the annual audit plan. Proactively identifying themes, trends, and emerging risks for the company
• Develop and maintain partnerships while working in a cross-functional team of Data Engineers, Product Owners, and Business Intelligence Analysts
• Exercise critical thinking and innovative problem solving