Boeing Research & Technology is looking for a Statistician to support The Applied Math Group in Tukwila, WA.
We are looking for a candidate with an advanced degree in applied mathematics or statistics.
Selected candidate would conduct statistical analysis of engineering problems and use statistical software applications as part of that analysis.
- Develop statistical models for engineering, business and manufacturing systems.
- Interact with customers to identify and define business or engineering problems and perform subsequent analysis.
- Analyze data using applications packages such as SAS and R.
- Generate and implement algorithms used for computer simulation experimentation and modeling.
- Create statistical criteria to be used in product and process testing.
Boeing is the world's largest aerospace company and leading manufacturer of commercial airplanes and defense, space and security systems. We are engineers and technicians. Skilled scientists and thinkers. Bold innovators and dreamers. Join us, and you can build something better for yourself, for our customers and for the world.
Engineering Test and Tech
Relocation Assistance Available
No. Relocation assistance is not a negotiable benefit.
This position must meet Export Control compliance requirements, therefore a “US Person” as defined by 22 C.F.R. § 120.15 is required. “US Person” includes US Citizen, lawful permanent resident, refugee, or asylee.
Basic Qualifications (Required Skills and Experience)
- An advanced degree (minimum Master's) in Statistics, Biostatistics, Applied Statistics or Applied Mathematics with research in statistics or computational statistics.
- More than 3 years experience in applied mathematics or statistics
- More than 3 years experience using SAS software (or equivalent) for data manipulation, analysis and modeling
- Experience conducting statistical analysis of engineering problems using statistical software applications
- Experience in lean product development, Success Assured methods and the Success Assured™ software, and the application of Scaled Agile
- Experience performing reliability analyses including mission reliability requirements/performance parameters, mean time between failure, predictions, allocations, mathematical modeling and statistical processing
- Experience in scientific/technical consultation on problems that require interaction with customers to identify and define business or engineering problems and perform subsequent analysis.
- Proven ability to grasp these types of problems and formulate, analyze, interpret, and communicate results to the business and engineering community.
- Knowledge of computational statistics with extensive experience with R for statistical analysis or substantial industry experience with SAS or other statistical software packages and an interest in learning R and Python.
- Expertise with statistical models, such as linear models, generalized linear models, and linear mixed models; multivariate statistics; reliability and time series methods; advanced knowledge of probability theory and mathematical statistics.
Preferred Qualifications (Desired Skills and Experience)
- Experience with Python for data handling.
- Ability to apply design of experiments and statistical process control to improve products and processes and create statistical criteria to be used in product and process testing.
- Understand of a wide range of statistical techniques with an application to business and engineering problems which may include: Regression Modeling (linear, robust, logistic and mixed models), ANOVA, MANOVA, Time Series Analysis, Bootstrap, Reliability, Uncertainty Quantification, Design of Experiments, Statistical Process Control, Acceptance Sampling, and Statistical Tolerancing.
Technical bachelor's degree and typically 5 or more years' related work experience or a Master's degree with typically 3 or more years' or a PhD degree or an equivalent combination of education and experience. A technical degree is defined as any four year degree, or greater, in a mathematic, scientific or information technology field of study.