Business Data Scientist

Idaho National Laboratory • Idaho Falls, ID

7d • $114,360 - $234,336 • Onsite

About The Position

Idaho National Laboratory is hiring a Business Data Scientist to work on our Nuclear Nonproliferation Division and the "Material Minimization, Security and International Safeguards team. Our team works a 9x80 schedule located out of our Idaho Falls facility with every other Friday off. This role involves applying advanced analytical technologies, collaborating with diverse teams, developing and operationalizing AI/ML solutions, and contributing to the enterprise advanced analytics roadmap. The position requires producing analytical results, visualizations, and decision-support materials across various computing environments, and developing custom analytical software. The role also includes assessing data quality, following cybersecurity policies, and serving as a subject matter expert in data science techniques.

Requirements

• Level 4: Bachelor’s degree + 9 years relevant experience OR Master’s degree + 6 years relevant experience OR PhD + 4 years relevant experience
• Level 5: Bachelor’s degree + 14 years relevant experience OR Master’s degree + 8 years relevant experience OR PhD + 6 years relevant experience
• Relevant Experience fields include Data Science, Computer Science, Mathematics, Statistics, or related disciplines
• Proficiency with tools and languages such as Python, R, SQL, Spark, SAS, Tableau, Excel, Jupyter Notebooks, and Azure Notebooks.
• Strong data visualization expertise and experience defining KPIs.
• Demonstrated ability to collaborate across diverse scientific and technical teams and facilitate cohesive decision‑making.
• Ability to communicate technical concepts clearly to both business and technical audiences.
• Experience mentoring or training staff in data analytics methods and workflows.
• Ability to obtain and maintain a DOE Q clearance (U.S. Citizenship required).

Nice To Haves

• Experience with cloud platforms and cloud‑native analytics (AWS, Azure, GCP).
• Experience with SciPy, PyTorch, TensorFlow, CUDA, notebook IDEs, NLP methods, graph databases, relational databases, and data storage architectures.
• Experience with version control and repository management (e.g., Git).

Responsibilities

• Apply advanced analytical technologies such as explainable AI/ML, large language models, physics‑informed ML, systems performance modeling, and multi‑sensor data fusion.
• Collaborate with domain scientists, engineers, business analysts, data owners, and data stewards to define analytical questions, validate data, identify informative features, and interpret model outcomes.
• Use high‑performance computing architectures and cloud platforms for data extraction, processing, modeling, and storage across structured and unstructured datasets.
• Develop, test, and operationalize machine learning and artificial intelligence solutions tailored to business and engineering applications.
• Produce analytical results, visualizations, and decision‑support materials across cloud, on‑premises, and edge computing environments.
• Contribute to and help lead the planning and execution of INL’s enterprise advanced analytics roadmap.
• Partner with cross‑functional teams to develop and manage technical programs and deliverables for a variety of internal and external customers.
• Develop and maintain analysis notebooks, software modules, scripts, and user‑facing applications that support business and engineering workflows.
• Work with software and database engineers to deploy robust, secure, and maintainable code to development, staging, and production environments.
• Build custom analytical software such as 3D visualization utilities, parallel computing workflows, batch processing scripts, and API‑driven integrations.
• Assess data quality issues, communicate findings to data providers, and design repeatable, traceable preprocessing pipelines.
• Employ state‑of‑the‑art modeling, simulation, statistical inference, and uncertainty quantification methods to support INL’s mission related to safety, reliability, resilience, and operational performance of engineered systems.
• Follow INL policies and standards related to cybersecurity, software development practices, and management of sensitive information.
• Serve as a subject matter expert in modern data science techniques including data mining, regression, ML/AI methods, natural language processing, and large‑scale analytics.
• Apply predictive, prescriptive, and probabilistic modeling methods to produce actionable insights and inform decision‑making.

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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior