Sabre Systems is currently recruiting for a Data Scientist to provide support for the NAWCAD Readiness & Fleet Analytics (R&FA) Division’s Advanced Analytics and Innovation (AA&I) Branch at Patuxent River Naval Air Station in Lexington Park, MD. The selected candidate will focus on developing advanced dashboards, visualizations, and websites, while leveraging data engineering, advanced analytics, and machine learning to analyze and manage complex datasets. The candidate will use business intelligence (BI) tools such as Tableau and Microsoft Power BI to transform PMA reliability, maintenance, and supply data into actionable insights. Additionally, you will work with cutting-edge data engineering, web development, and data science platforms, including Databricks, GitLab, JIRA, Amazon Web Services (AWS), NUCLEUS, and JAVA, to deliver innovative and impactful solutions. The AA&I Branch provides critical support to Program Management Air (PMA) offices, the Air Systems Group, Command, Fleet Readiness Centers, and other Department of Defense (DoD) services. This is a full-time position with telework as the primary arrangement. The selected candidate will be responsible for but not limited to: Apply advanced analytical models, techniques, and methodologies to solve complex scientific and business operations challenges. Dashboard & Visualization Development: Research, design, and develop user-centric interactive reports, dashboards, and visualization solutions using Tableau, Qlik, or Power BI to deliver actionable business insights for PMA and AA&I branch decision makers. Technical Proficiency & Analysis: Demonstrate expertise in scientific tools including QLIK, Tableau, R, Python, and SQL, along with other programming and dashboarding utilities. Analyze aircraft platforms and develop algorithms to detect system failures and performance issues. Data Engineering & Architecture: Design, build, integrate, and manage data architecture and frameworks for various data science projects, ensuring seamless data flow between servers and applications. Data Management & Processing: Gather, clean, preprocess, and analyze data from multiple sources to support modeling and decision-making processes. Apply statistical analysis and data mining techniques to extract insights, validate model assumptions, and develop automated scripts for data transmission across different environments. Advanced Analytics: Apply machine learning, natural language processing, and other advanced programming techniques to collect, process, analyze, and present statistical data in meaningful formats. Predictive Analytics: Analyze historical data and trends to forecast future outcomes and continuously optimize model performance.
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Job Type
Full-time
Career Level
Mid Level