Data Scientist II

Lead and support moderate to highly complex data science and analytics projects in support of process improvement, defect reduction, and predictive analytics for manufacturing and business applications. Independently develop solutions 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 and communicate directly with key stakeholders 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. Strong analytical skills with experience with data mining and modeling. Develop and implement machine learning models to inform business needs and decisions. Perform data processing and transformation to targeted audience.

BS in engineering from ABET accredited institution or Bachelor of Science degree in data science or related field, or two years of relevant experience in lieu of a degree. Two or more years of relevant experience in data science or related technical activities. Ability to travel as determined by the needs of the business Ability to work remote, hybrid, or on-site as directed by management and is determined by the needs of the business Regular and reliable attendance is an essential function of this job United States Citizenship Ability to obtain and maintain a U.S. Department of Energy (DOE) security clearance (some positions require additional DOE designations)

We Value Working knowledge of statistics, statistical modeling, and statistical process control. Practiced 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. Experience producing analytics data visualizations, preferably using Tableau, MicroStrategy, or equivalent. Experience working with Hadoop, Hive, Apache Spark, etc. Experience with machine learning, neural networks, deep learning. Experience using open-source data analytics and machine learning tools along with other cloud-based platforms. This job description/job posting is not all inclusive and other duties may be assigned.

We are focused on attracting, hiring and retaining talented people who power our mission. Our robust total rewards package recognizes performance, fuels development and supports flexibility. Key features include:

Medical, dental and vision insurance

Health Savings Account (HSA)

Industry leading 401(k) match

Generous paid time off

Flexible work schedule

Tuition Reimbursement

The Kansas City National Security Campus (KCNSC), managed and operated by Honeywell Federal Manufacturing & Technologies, is a premier advanced manufacturing facility that supports the safety, security, reliability and effectiveness of our nation's nuclear deterrent. With nearly 7,000 employees combined in Kansas City, Missouri, and Albuquerque, New Mexico, KCNSC protects our nation and allies by producing trusted national security products and services for the U.S. Department of Energy's National Nuclear Security Administration. We create innovative solutions to complex national security challenges, and lead with accountability, collaboration and an unwavering dedication to our mission and core values. Are you ready to do work that matters? SummaryContribute your expertise in data science to support KCNSC's national security mission. Responsible for leveraging advanced analytics and machine learning techniques to extract meaningful insights from large datasets. Collaborate with cross functional teams to develop solutions which address business needs.