Research Data Scientist at Idaho… · Idaho…

Summary: Idaho National Laboratory is a science-based, applied engineering national laboratory dedicated to supporting the U.S. Department of Energy's mission in nuclear energy research. They are seeking a Research Data Scientist to analyze data across various computational architectures and apply advanced technologies to support research objectives, collaborating with multi-disciplinary teams and publishing results in peer-reviewed journals. Responsibilities: - Analyze data and generate results in response to data analytics, visualization, and modeling needs on a variety of computational architectures (cloud, on-premises, edge-based) - Apply advanced technologies, such as Explainable Artificial Intelligence/Machine Learning (AI/ML), Large Language Models (LLMs), physics-informed machine learning, systems performance analysis, and/or data sensor fusion methodologies - Work with a multi-disciplinary team of scientists and engineers on challenging work scopes - Demonstrate effective research skills and the ability to collaborate and partner with other government agencies, academia, and private sector companies to achieve project goals - Publish results of research and development in a mix of refereed publications and conference proceedings - Work effectively with other research teams to develop and manage cross-cutting technical programs for a variety of customers - Develop and maintain notebooks, software, and/or applications - Work with software and database developers to develop, test, and deploy software code to development, staging, and production environments - Develop software for custom solutions, including but not limited to, 3D visualization tools, parallel software, batch scripting, and web API interaction/development - Analyze data quality, characterize, and communicate data quality issues to data providers, and design repeatable data processing procedures to accurately analyze data in the presence of quality issues - Work with domain experts to understand the scope and limits of questions that can be answered by data sets, identify key data features as inputs to analysis, and design output metrics that elegantly describe system attributes and behavior - Employ specialized methods and state-of-the-art data analysis and modeling tools to support INL's mission by ensuring the nation’s safe, competitive, and sustainable use of engineered systems in many domains by applying capabilities to impactful issues in risk, reliability, and operational performance - Adhere to INL policies and lab-wide procedures related to software development, cybersecurity, and management of sensitive information and data - Work with data providers, database administrators, and software developers to diagnose and solve problems with data and software systems quickly and effectively Required Qualifications: - Level 1: Bachelor's degree of Science degree in data science, engineering, mathematics, computer science, physics, autonomy, artificial intelligence, or related technical discipline - Level 2: Masters of Science degree in data science, engineering, mathematics, computer science, physics, autonomy, artificial intelligence, or related technical discipline - Working knowledge in data science, data analysis, and software development using Python, C#, Java, or C++ - Ability to collaborate in Python and GitHub environments, Large Language Model implementation, RAG development Preferred Qualifications: - Experience with cloud services and cloud-based analytics (AWS, Azure, or Google Cloud Platform, etc.) - Experience with SciPy, Notebook IDE, PyTorch, TensorFlow, Cuda, Natural Language Processing Techniques, Graph Databases, Relational Databases, and a general understanding of data storage and processing Required Skills: Data Science, Python, Machine Learning Important Skills: Cloud Services, Data Analysis, Software Development Nice-to-Have Skills: Research Skills Benefits: Medical, Dental, Vision, and Flexible Spending Accounts, 401(k) with a 4.2% employer contribution and up to 4.8% match (regular positions) or self-contribute access (postdoctoral positions), Paid time off (personal leave), Employee Education Program (tuition assistance for eligible positions), Comprehensive Relocation Package