Pacific Northwest National Laboratory - Richland, WA
posted 3 months ago
The Risk Visualization Data Scientist 1 position at Pacific Northwest National Laboratory (PNNL) is an early-career role within the Earth System Science Division, which focuses on solving complex problems related to energy independence and national security through advanced earth systems science and decision analytics. The successful candidate will engage in a variety of programmatic risk projects, utilizing their expertise in risk management and data modeling to contribute to the understanding and mitigation of operational risks at the interface of human and natural environments. This includes predicting the impacts of natural hazards and extreme climate events on both Earth and human systems, as well as addressing issues related to environmental contamination and the sustainability of water resources. In this role, the candidate will be expected to conduct quantitative analyses, such as schedule risk analysis or using in-house material production risk models. They will work independently with minimal oversight, developing or contributing to technical risk-related products while adhering to quality, timeliness, and cost guidelines set by project managers. Effective communication of uncertainty concepts and results is crucial, as the candidate will contribute to the preparation of high-quality presentations and reports. This position is designed for individuals who have a conceptual understanding and practical experience in data science, and who are eager to improve risk analysis products through best practices. The ideal candidate will demonstrate a self-motivated and self-directed approach to their work, with a strong foundation in quantitative risk modeling and analysis methods. They will be part of a team that emphasizes a “science-to-solutions” philosophy, providing scientific leadership and technology to enhance national security and optimize disaster response. The work environment at PNNL is dynamic and collaborative, offering opportunities to engage with renowned researchers and contribute to meaningful scientific outcomes.