Innovate to solve the world's most important challenges

Honeywell is a Fortune 100 company that invents and manufactures technologies to address critical challenges linked to global macrotrends such as safety, security, productivity, global urbanization and energy. With approximately 129,000 employees worldwide, including more than 19,000 engineers and scientists, Honeywell has an unrelenting focus on quality, delivery, value, and technology in everything they make and do. Honeywell has been named a Top 100 Global Innovator for seven years in a row, recognizing the company’s global reach of portfolio and invention influence.

In Kansas City, Honeywell Federal Manufacturing & Technologies (FM&T) manages and operates the U.S. Department of Energy/National Nuclear Security Administration’s (NNSA) Kansas City National Security Campus. This state-of-the-art engineering, manufacturing and sourcing facility produces a wide array of intricate components to deliver trusted national security products and government services primarily for the NNSA. Honeywell FM&T’s culture of integrity, commitment and continuous improvement enables them to deliver responsive, collaborative, and innovative management and technology services and products that translate into cutting edge solutions to complex national security issues.

***This position will be in Kansas City, MO***

Summary of Duties:

• Lead moderate to highly complex data science and analytics projects that require skills in a diverse array of data science applications to support process improvement, defect reduction, and predictive analytics for manufacturing and business
• Responsible for problem analysis, customer interaction, solution design, front end and back-end integration, maintenance, and support of data science and analytics solutions
• Independently develop data science models or algorithms using disciplined software development processes, making recommendations for developing new code or re-using existing code, implementing version control, and maintaining documentation of created applications
• Work directly with customers and business partners to develop requirements and provide technical solutions through an analysis of manufacturing/business needs and pain points.
• Define and implement ingestion, data preparation, curation, and governance of large, multi-faceted data sets supporting analytics models and workflows
• Contribute to the production of information products, supporting visualization and data accessibility in a customer centric manner
• Evaluate and make recommendations regarding technical advances that improve productivity and quality, reduce flow times, and enhance operational surety
• Develop guidelines and standards for analytics and machine learning models, their deployment, and associated processes