Data Scientist

The Department of Energy's mission is to ensure America's security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions.

The Office of Science - Headquarters office works to support and oversee research facilities and programs that cover basic science through its application to the demonstration and deployment of energy technologies. The Office of Science oversees 10 of the 17 Department of Energy (DOE) National Labs and 28 major federal research user facilities.

Its mission is to preserve U.S. leadership in science, fund and perform basic research, and provide the scientific facilities that the private sector is unable or unwilling to provide.

We are truly honored that DOE has been named America's #1 Best Employer for Veterans in 2023 by Forbes-not only among Government agencies, but among employers across the U.S. We are so proud of this ranking which reflects our commitment to the employment of veterans.

As so many veterans at DOE renew their service to our Nation, we are deeply committed to their success and advancement.

Veterans shape the future of energy As a Data Scientist, you will: Develop, implement, and maintain a data-driven enterprise risk management (ERM) framework and supporting datasets to identify, assess, prioritize, and advise on mitigation strategies for operational, safety, and security risks across all Office of Science sites and national laboratories.

Provide projects with technical leadership, project management, and strategic direction to apply advanced data science lifecycle principles-such as data collection, cleaning, modeling, and machine learning-on enterprise datasets.

Design, deploy, and maintain data visualization tools, dashboards, predictive models, and quantitative risk indicators to translate complex analytical findings into actionable decision support, briefing materials, and budget formulations for program leadership.

Serve as a subject matter advisor to leadership on applying AI to operations, direct AI initiatives from concept to deployment, and align agency projects with Department of Energy strategies and policies.

Represent the office in department-wide forums and working groups to convey programmatic data needs, share insights on data governance and AI, and collaborate with internal and external stakeholders to improve enterprise data quality.

BASIC REQUIREMENT: Degree: Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.

OR Combination of education and experience: Courses equivalent to a major field of study (30 semester hours) as shown in paragraph A above, plus additional education or appropriate experience.

GS-14 SPECIALIZED EXPERIENCE REQUIREMENTS: A qualified candidate's online application and resume must demonstrate at least one year of specialized experience equivalent to the next lower grade level GS-13 in the Federal service.

Specialized experience for this position is defined as meeting ALL of the following: Developing complex statistical models, data mining processes, or machine learning algorithms using advanced programming languages (such as Python, R, or SQL) to extract patterns and insights from large, varied datasets.

Maintaining quantitative performance scorecards, enterprise risk indicators, or trend-analysis tracking systems to evaluate the operational health, safety, or efficiency of an organization. Coordinating database development, or artificial intelligence (AI) projects from the initial concept phase to a fully operational status.

GS-15 SPECIALIZED EXPERIENCE REQUIREMENTS: A qualified candidate's online application and resume must demonstrate at least one year of specialized experience equivalent to the next lower grade level GS-14 in the Federal service.

Specialized experience for this position is defined as meeting ALL of the following: Deploying complex statistical models, data mining processes, or machine learning algorithms using advanced programming languages (such as Python, R, or SQL) to extract patterns and insights from large, varied datasets.

Designing quantitative performance scorecards, enterprise risk indicators, or trend-analysis tracking systems to evaluate the operational health, safety, or efficiency of an organization. Scheduling database development, or artificial intelligence (AI) projects from the initial concept phase to a fully operational status.

Limit your resume to no more than two (2) pages. If more than two pages are submitted, only the first two pages will be reviewed to determine your eligibility and qualifications. Your full resume will be made available to the hiring manager if you are referred. "Experience" refers to paid and unpaid experience.

Examples of qualifying unpaid experience may include: volunteer work done through National Service programs (such as Peace Corps and AmeriCorps); as well as work for other community-based philanthropic and social organizations.

Volunteer work helps build critical competencies, knowledge, and skills; and can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.

Time-in-Grade: Current Federal employees must meet time-in-grade requirements by the closing date of this announcement to receive consideration.

CTAP/ICTAP candidates: To be considered "well qualified" you must (1) meet all of the requirements as described in this section; and 2) be rated "well-qualified", which is defined as having a score of 85 or better. You must meet all qualifications and eligibility requirements by the closing date of this announcement.