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Senior Data Analytics Engineer - 2556C - Employee Referral Eligible

Arnold AFB, TN · Government/Military
Job Title: Senior Data Analytics Engineer - 2556C
Function: Engineering
Position Type: Regular, Full-Time                                 
Pay Type: Exempt                        
Grade:  37-38
US Citizenship Required


National Aerospace Solutions (NAS), LLC is the team selected by the U.S. Air Force (USAF) to conduct Test and Operations Sustainment activities at the Arnold Engineering Development Complex (AEDC), Arnold Air Force Base, in Tullahoma, Tennessee. NAS is committed to partnering with the Air Force and the workforce at AEDC to drive the change necessary to ensure the long-term viability of the Complex while ensuring mission success: no impact to customers, no loss in data quality, and no reduction in productive test time – ultimately securing AEDC's long-term future and world-class superiority in aerospace and flight testing.

Job Summary:
This job is to develop and apply statistical and modern analytical methods to improve operations and maintenance of the AEDC air and space ground test equipment and facilities. The successful candidate will work as a member of the Reliability Engineering group in the Asset Health Assurance (AHA) Branch to lead implementation of data-centered projects to improve the AEDC ground test infrastructure, facility operations, and business systems. The person selected for this role will work closely with multidisciplinary work teams throughout the NAS organization to identify opportunities for leveraging data to drive decisions and will help design and implement a data architecture working with database administrators and reliability engineers in the AHA Branch.

Job Duties:
  • Work with AHA Reliability Engineering section manager for the development and implementation of data-analytics strategy and program for the AHA branch
  • Utilize facility multiple data sources such as data Historian and business systems data to optimize operations and maintenance at AEDC and suggest ways which insights obtained might be used to inform infrastructure sustainment and operational strategies.
  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  • Develop approaches and  demonstrate abilities to mine and analyze data from databases to drive optimization and improvement of operations and maintenance at AEDC
  • Identify and assess the effectiveness of new data analytics approaches, data sources and data gathering techniques
  • Develop custom data models and algorithms to apply to data sets
  • Use predictive modeling to increase component and system reliability,  guiding better use of labor and dollar resources directed at the highest priority operations
  • Coordinate with different multidisciplinary teams to implement models and monitor outcomes
  • Present information with effective visualization techniques.
  • Develop processes and tools to monitor and analyze model performance and data accuracy
  • Develop the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and ‘big data’ technologies
  • Perform analysis on machinery failure data and work order processes, recommend adjustments where warranted
  • It is a condition of employment to wear company issued PPE (Personal Protective Equipment) in accordance with supervisory direction and company policy 
  • Performs other related duties as required

Basic Qualifications:
  • B.S. in Computer Science, Statistics, Mathematics, Engineering or another relevant engineering field from an accredited university plus a minimum of 12 to 14  years of progressive and relevant experience
  • Experience with data scripting languages or statistical/mathematical software to support probability and correlation analyses approaches.
  • Current U.S. Citizenship is required.

Preferred Qualifications
  • Master’s or PhD degree in Computer Science, Statistics, Mathematics, Engineering or another relevant engineering field from an accredited university
  • Demonstrated experience in a data analytics role applied to technical data in probability analyses and statistical analytics to gain insights using large data sources.
  • Knowledge of data mining, analysis and collection techniques applied to operations and analysis, especially safety or operations process improvement.
  • Experience using statistical computer languages (R, Python, SQL, etc.) to analyze data and draw insights from large data sets.
  • Experience working with and creating data architectures.
  • Experience performing root cause analysis.
  • Knowledge of a variety of machine learning techniques and their real-world advantages/drawbacks.
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
  • Coding knowledge and experience with multiple languages
  • Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, etc.
  • Good interpersonal and communication skills, both written and verbal, including the preparation of technical reports is required

Due to Air Force Security requirements, U.S. Citizenship is required for employment at AEDC.
 
NAS is an Equal Opportunity Employer of Minority/Women/Veterans/Disabled (AA/EOE). All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, sexual orientation, gender identity and expression, pregnancy, physical or mental disability, citizenship, genetic information, protected veteran status or any other characteristic protected by federal, state or local law.

Applicants with a physical or mental disability, who require a reasonable accommodation for any part of the application or hiring process, may e-mail their request to careers@nas-llc.us.

PLEASE DO NOT SUBMIT RESUMES to this address as they will not be considered for employment opportunities.
 
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