Job at Department of Energy Headquarters
Data Scientist
- Employer
- Department of Energy Headquarters (U.S. Federal Government)
- Location
- Billings, Montana · Folsom, California · Lakewood, Colorado · Salt Lake City, Utah
- Workplace
- Not supplied
- Employment
- full-time
- Department
- Department of Energy Headquarters
- Team
- Department of Energy
- Salary
- $89,508 to $154,280 per year, as the employer lists it
- Published
- First listed on USASI
This posting comes from USAJOBS.gov, the U.S. federal government’s official employment site. The hiring agency is Department of Energy Headquarters. USASI checks USAJOBS and removes this page once the announcement closes. The description below is the agency’s text as published; USASI does not edit it, does not recruit, and does not take applications. How jobs are collected.
Job description
This position is part of the Office of the Chief Human Capital Officer - Power Marketing Administration HR Shared Service Center, Department of Energy. As a Data Scientist, you will drive strategic workforce solutions by developing advanced analytical models and providing data-driven counsel to management on Human Resource optimization and planning. **This is not a remote position. The selectee will be required to be physically present at one of the duty location(s) identified.**
Duties
As a Data Scientist, you will: Lead the strategic vision and execution for HR analytical tool development and deployment. Design and implement advanced workforce predictive and analytical tools. Develop scalable automated reporting pipelines, high-fidelity dashboards, and custom platforms that inform strategic recommendations for complex workforce challenges. Conduct comprehensive studies in workforce planning, position management, and strategy development, leveraging advanced predictive, prescriptive, and diagnostic analytics to uncover insights, forecast trends, and simulate policy impacts. Provide expert technical assistance and guidance on advanced data analysis, statistical techniques, experimental design, and effective utilization of new data science tools. Lead engagements with various personnel across DOE, Human Capital, and the PMAs to identify advanced analytical techniques and methods for workforce planning and strategy.
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