Test Engineering Data Scientist

Key Skills

Algorithms, Data science techniques, Data Visualization, Effective communication skills, Machine learning techniques, Python Programming, R Programming, SQL

Job Description

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.

Primary Responsibilities:

• Lead minimally complex or support moderately complex data science and analytics projects, aimed at process improvement, defect reduction, and predictive analytics for manufacturing and business applications.
• 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 provide technical solutions through an analysis of manufacturing/business needs and pain points.
• Support the 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.
• May assist in development of guidelines and standards for analytics and machine learning models, their deployment, and associated governance processes.
• Conducts activities in a safe and healthy manner and works in accordance with established HS&E requirements to ensure the protection of employees, the public, and the environment.
• Takes actions necessary to 'stop' work when an unsafe condition or action is identified. Every employee has the right and responsibility to stop work when unsafe conditions or actions are identified.
• Complete assignments with detailed instructions in the design and/or project management of new and current projects under technical guidance of higher level engineers or departmental management.

You Must Have:

• BS in engineering from ABET accredited institution or Master’s degree in data science or related field, or two years of relevant experience in lieu of a degree.
• No prior experience is required.
• Demonstrated analytical skills, proficient with computer software applications, and the ability to produce and consume written documentation.

We Value:

• Previous relevant internship experience preferred.
• Basic understanding of statistics and statistical process control.
• Comfortable using scripting and querying languages such as Python, R, SQL, and others.
• Effective communication skills (verbal, written, and presentation) for interacting with customers and peers.
• User experience mindset, including the production of visualizations and infographics to distill complex information.
• Interest in applied Data Science career in a technology or manufacturing business.