The DPHM team is looking for an innovative experienced senior engine performance engineer and data scientist that can apply numerical methods to complex turbomachinery systems operating in service.
The candidate will develop solutions that provide automated diagnostic and prognostic capabilities to identify shifts / deterioration in the engine s major mechanical systems, such as the following :
- Overall Engine Performance
- Oil System Health
- Fuel System Health
- Start System Health
- Vibration
Additionally, the candidate will work actively with the Ground Systems engineering and Customer Service teams, in optimizing end to end data pipeline performance and introduction of new engine health management solutions.
Required qualification and skills :
Bachelor / Master of Science in Aerospace, Mechanical or Software Engineering with minimum 8-12 years of engineering experience required in the field of aviation.Strong knowledge of software development process and software development tools (incl. C / C++ and Python)Extensive experience in advanced ML / statistical techniques such as regression analysis, predictive modeling, time series analysis, classification, clustering, feature reduction etcAbility to leverage analytical and quantitative skills to use data and metrics to back up assumptions, compare against physics-based models and complete root cause analysisStrong oral and written communication skills in EnglishUnderstanding aircraft engine performance and aerodynamics, sizing, cycle analysis and / or preliminary design analysisGood understanding of turbine engine control systems, aircraft avionics systems, requirements writing and software configuration management practicesStrong knowledge of Excel, Python, SQL, AWS Lambda, PowerBI is mandatoryExperience running engine performance (such as NPSS, FAST, SOAPP, etc) or data reduction modelsKnowledgeable of Six Sigma Control Charts and the associated statisticsExperience troubleshooting turbomachinery systems.Beneficial Skillsets : AWS Services, DataBricks, Machine Learning, Agile Framework and knowledge of Product Reliability analysisRole and responsibilities :
Support development and implementation of advanced engine performance condition trend monitoring algorithms for all PWC engine types and modelsPerform aero-thermodynamic cycle analysis and make aircraft engine performance trend predictions by creating deterioration models and simulationsInvestigate system level issues related to aircraft gas turbine engine design, performance, operability and operationGenerate algorithms that normalize engine data to a consistent operating condition for trendingDevelop and implement scripts, algorithms, machine learning, data clustering and fault classification techniques within a relational database structureCreate, validate and implement advanced aircraft utilization algorithms and engine performance trend monitoring tools to enhance engine maintenance forecasting accuracyParticipate and present in technical reviewsPerform database queries to support engineering analysis and manage engine field issuesSupport implementation of dashboards and BI solutions for internal and external customer reportingSkills Required
Aws Lambda, C, Powerbi, C C++, Excel, Python, Sql