Senior Engineer, Data Analytics

Unspecified Who we are: Pratt & Whitney, an RTX business, 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 ready to 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: Develop and implement advanced AI and machine learning models for engine condition monitoring, fault detection, and predictive maintenance. Apply machine learning techniques such as classification, clustering, anomaly detection, and time series forecasting to analyze engine performance and operational data. Collaborate with engineering and data teams to integrate AI/ML insights into digital engine diagnostics and prognostics platforms. Create and optimize scalable data pipelines and workflows for processing large volumes of sensor and operational data. Design and maintain interactive dashboards and visualization tools (Power BI, Matplotlib, HighCharts) to communicate AI-driven insights effectively. Perform exploratory data analysis to identify trends, patterns, and actionable insights using statistical and machine learning methods. Work with relational databases (MS SQL, MySQL, PostgreSQL) and big data technologies (Databricks, AWS) to manage, clean, and preprocess datasets. Document machine learning workflows, model evaluation metrics, and deployment processes for reproducibility and continuous improvement.  Qualifications You Must Have: Bachelor’s or Master’s degree in Data Science, Computer Science, Aerospace Engineering, Mechanical Engineering, or a related field. Minimum 5-8 years of experience applying AI and machine learning in an engineering or industrial setting. Strong programming skills in Python and/or R, with experience using machine learning libraries and frameworks such as Scikit-learn, TensorFlow, Keras, or PyTorch. Proficient in SQL and experience working with relational databases (MS SQL, MySQL, PostgreSQL). Experience building and deploying machine learning models in cloud environments, preferably AWS (SageMaker, Lambda, S3). Knowledge of data engineering tools and platforms such as Databricks, Airflow, or similar ETL/ELT frameworks. Skilled in data visualization using tools like Power BI, Matplotlib, and HighCharts. Understanding of statistical analysis, hypothesis testing, and time series analysis. Strong communication skills with the ability to present complex AI/ML concepts to technical and non-technical stakeholders.  Beneficial Skills: Familiarity with turbomachinery or aerospace data is a plus but not mandatory. Experience with predictive maintenance and condition-based monitoring systems. Understanding of digital twin concepts and their application in aerospace or industrial settings. 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