Principal Engineer, Data Analytics

Unspecified Who we are: Pratt & Whitney is working to once again transform the future of flight—designing, building, and servicing engines unlike any the world has ever seen. And because transformation begins from within, we’re seeking the people to drive it. So, calling all curious. Come ready to explore and you’ll find a place where your talent takes flight—beyond the borders of title, a country, or your comfort zone. Bring your passion and commitment and we’ll welcome you into a tight-knit team that takes our mission personally. Channel your drive to make a difference into shaping an organization and an industry that’s evolving fast to the future. At Pratt & Whitney, the difference you make is on display every day. Just look up. Are you readyto go beyond? What are our expectations: 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. What You Will Do: Support development and implementation of advanced engine performance condition trend monitoring algorithms for all P&WC engine types and models Perform aero-thermodynamic cycle analysis and make aircraft engine performance trend predictions by creating deterioration models and simulations Investigating system level issues related to aircraft gas turbine engine design, performance, operability and operation Generate algorithms that normalize engine data to a consistent operating condition for trending Develop and implement scripts, algorithms, machine learning, data clustering and fault classification techniques within a relational database structure Create, validate and implement advanced aircraft utilization algorithms and engine performance trend monitoring tools to enhance engine maintenance forecasting accuracy Participate and present in technical reviews Perform database queries to support engineering analysis and manage engine field issues Support implementation of dashboards and BI solutions for internal and external customer reporting Qualifications You Must Have: Bachelor/Master of Science in Aerospace, Mechanical or Software Engineering with minimum 8-12 years of engineering experience required in the field of aviation. Understanding aircraft engine performance and aerodynamics, sizing, cycle analysis and/or preliminary design analysis Good understanding of turbine engine control systems, aircraft avionics systems, requirements writing and software configuration management practices Experience running engine performance (such as NPSS, FAST, SOAPP, etc.) or data reduction models Strong knowledge of computing deterioration rates using field data and conducting modular performance study Experience troubleshooting turbomachinery systems along with field event analysis and event reliability studies Develop/Deploy prognostic indicators for key reliability drivers and map to the trend symptoms Ability to leverage analytical and quantitative skills to use data and metrics to back up assumptions, compare against physics-based models and complete root cause analysis Ability to leverage analytical and quantitative skills to use data and metrics to back up assumptions, compare against physics-based models and complete root cause analysis Strong knowledge of Excel, Python, SQL, AWS Lambda, & PowerBI is mandatory Knowledgeable of Six Sigma Control Charts and the associated statistics Strong oral and written communication skills in English Beneficial Skillsets: AWS Services, DataBricks, Machine Learning, Agile Framework and knowledge of Product Reliability analysis 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 etc. What we offer Long-term deferred compensation programs Daycare for young children Advancement programs to enhance education skills Flexible work schedules Leadership and training programs Comprehensive benefits, savings, and pension plans Financial support for parental leave Reward programs for outstanding work