Aerodynamics Engineer – Data Science

Aerodynamics Engineer – Data Science

Requirements

• BS or higher degree in Aerospace Engineering or Data Science
• Understanding of fluid mechanics, aerodynamics and flight dynamics
• 2+ years experience deploying ML models in an engineering related framework
• Strong programming skills in higher-level languages (Python, Matlab) in a version-controlled environment (preferably git) and comfortable with low level languages (C, C++, Fortran)
• Experience deploying ML frameworks such as TensorFlow, Keras, or PyTorch
• Familiarity with various ML models, including: Geometric Neural Nets, Transformers, XGBoost and Random Forest, RNN, KNN, PCA, DBSCAN
• Experience building end-to-end data science pipelines, including data aggregation, transformation, and model deployment
• Passion for defending the United States and her allies
• Ability to obtain and hold a U.S. Top Secret security clearance

Responsibilities

• Aerodynamic analysis of unmanned air vehicles, using both low and high order methods
• Apply ML concepts on engineering data to accelerate aerodynamic, structural and thermal analysis
• Develop various Data Science and ML tools to improve early stage MDAO trade space efforts
• Develop automated pipelines for training ML models with CFD or FEA data
• Apply data science techniques to build robust aerodynamic databases

Preferred Qualifications

• Degrees in both Aerospace Engineering & Data Science
• A strong desire to apply data science and ML methods across multiple engineering disciplines
• Experience with aircraft sizing and configuration trade studies, including aerodynamic design, shaping, and multidisciplinary design analysis and optimization (MDAO)
• Experience with transonic and supersonic flow regimes
• Experience with a variety of aerodynamic analysis techniques including hand calculations, vortex lattice methods, panel methods, and computational fluid dynamics (CFD)
• Active U.S. Secret security clearance