Pacific Northwest National Laboratory Buildings Data Scientist (Richland, WA or Arlington, VA) in RICHLAND, Washington
Organization and Job ID
Job ID: 308683
Directorate: Energy & Environment
Division: Electricity Infrastructure & Buildings
Group: Buildings & Connected Systems
The Pacific Northwest National Laboratory (PNNL)’s Buildings & Connected Systems Group is seeking a Data Scientist with strong computer science skills to support applied research into methods and technology solutions that enhance building efficiency and site-level energy and water resilience. This position offers the opportunity to perform data-driven research and discovery, facilitated by tools and techniques of machine learning and computational modeling, to produce knowledge about building performance, control system optimization and power systems intergration. PNNL is seeking candidates with strong computer science and programming skills, practical experience analyzing and gleening insights from building system data, and a solid understanding of theory underlying mechanical engineering, computer science and data science. The ideal candidate will have a passion for learning, innovation, and the field of building energy performance, and will bring a collaborative and creative approach to problem-solving. This position may be based in Richland, WA or in Arlington, VA.
Specific duties will include:
Supporting projects with systems engineering, software engineering, model integration, and development of production quality, as well as cloud-based software systems that help transition building-science technology to governmental, commercial, and residential consumers.
Contributing to multiple projects simultaneously and working in a dynamic team environment with high expectations for quality and on-time delivery.
Selecting preliminary technical approaches on assignments and work with senior engineers to refine approaches as needed on complex problems.
Contributing to the technical content related to computer science and data science to the support the development of technical products such as journal articles, technical reports, and conference presentations.
Contributing new ideas for proposals and project development opportunities.
Mentoring of junior staff and research associates.
Interacting effectively with funding sponsors.
The candidate must have BS/BA with 2 or more years of experience, MS/MA or PhD with 0 years of experience.
Master’s or PhD degree and in computer science or data science related field preferred.
Demonstrated Interest, curiosity and technical depth to support the development and advancement of applied problems specific to building operational efficiency and site-level energy and water resilience.
Ability to work effectively on project teams across technical groups and domains (e.g. data science, mechanical engineers, power systems engineers).
Well-developed oral and written communication skills wth the ability to convey complex technical information accurately and connect with diverse technical and non-technical audiences.
Ability to efficiently program in multiple programming languages such as Python, R, Java, Scala, etc., and use libraries such as SK-learn and Keras.Familiarity with mathematical software such as Matlab and Mathematica.
Experience applying these skills to building meter data, building control system data, and/or other power system and utility data streams.
Willingness to travel domestically periocially.
Equal Employment Opportunity
Battelle Memorial Institute (BMI) at Pacific Northwest National Laboratory (PNNL) is an Affirmative Action/Equal Opportunity Employer and supports diversity in the workplace. All employment decisions are made without regard to race, color, religion, sex, national origin, age, disability, veteran status, marital or family status, sexual orientation, gender identity, or genetic information. All BMI staff must be able to demonstrate the legal right to work in the United States. BMI is an E-Verify employer. Learn more at jobs.pnnl.gov.
Directorate: Energy & Environment
Job Category: Scientists/Scientific Support
Group: Building & Connected Systems
Opening Date: 2018-12-05
Closing Date: 2018-12-29