Description

Summary The Data Scientist II will lead moderately complex data science projects that require skill in a diverse array of data science applications. Responsible for problem analysis, customer interaction, solution design, front end and back end integration, maintenance, and support of data science and analytics solutions. Duties and Responsibilities 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 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. 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. 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. Two or more years of relevant experience in data science or related technical activities. Demonstrated analytical skills, proficient with computer software applications, and the ability to produce and consume written documentation. We Value Some experience with web-based applications and other electronic training and communications tools is preferred. Demonstrated ability to communicate effectively at all levels of the organization. Exceptional writing skills including the ability to develop clear and concise documents, articles and training materials. Ability to manage the resources required for project implementation. Creativity, energy, dependability and organizational skills that will enable successful management of multiple priorities. Strong interpersonal skills and demonstrated team participation and leadership. Experience dealing with cross-functional, cross-business, and global teams to deliver work products is a plus. Comfortable with a high degree of responsibility coupled with initiative, capacity to work independently and dedication to producing high quality work product. Some experience to manage to budget and schedule. Excellent written and oral communication skills. Strong organizational skills: managing several complex initiatives simultaneously in a fast-paced, demanding environment.

Role and Responsibilities

• Duties and Responsibilities 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 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. 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.