What are the responsibilities and job description for the Data Science Engineer for Turbomachinery Control System position at honeywell?
Data Science Engineer for Turbomachinery Control System
Location: Des Moines, Iowa- Relocation assistance available if qualified
A challenging and rewarding opportunity to join a leading company in the field of turbomachinery and data science.
Honeywell International Inc. (Nasdaq: HON) invents and commercializes technologies that address some of the world’s most critical challenges around energy, safety, security, air travel, productivity, and global urbanization. At CCC we develop mission critical control system for turbomachinery control applications deployed worldwide.
As a data scientist, you will be responsible for ideating, designing, and developing advanced solutions with the goals of improving asset reliability, efficiency, and performance through analysis of turbomachinery operational data. Examples of such time-series data includes continuously collected pressure, temperature, flow, actuator position, etc. You will collaborate with technology team to design the data infrastructure and interfaces, integrating with CCC control system and wider plant environment. You will develop statistical and machine learning analytical models and visualization dashboards, allowing end users to easily extract insights and actionable recommendations.
Key Responsibilities
· Design system architecture and components for data analytics integrating into existing turbomachinery control system.
· Develop, test, and deploy scalable and robust data pipelines and analytical models using Python, SQL, Spark, Pandas, and other tools and frameworks.
· Implement solutions that leverage appropriate data pre-processing statistical analysis, and machine learning techniques, such as regression, classification, clustering, anomaly detection, and forecasting, to address various use cases, such as performance optimization, fault diagnosis, predictive maintenance, and anomaly detection.
· Design and prototype intuitive data visualization methods.
· Stay updated with the latest developments and trends in the field of turbomachinery and data science, and identify new opportunities and challenges for data-driven decision making.
