Supervisory Data Scientist.

This position is located in Portland, OR—a city known for its expansive greenery, bike-friendly streets, efficient public transit, and vibrant culture. From the Portland International Rose Garden to lively festivals, diverse food, and proximity to the Portland Trail Blazers, there’s always something new to experience in this eco-friendly community.

About the role

As a Supervisory Data Scientist, you will serve as the key policy formulator and decision-maker for long- and short-range strategic data science, machine learning, and advanced analytics planning in support of the Bonneville Power Administration’s (BPA) mission.

• Act as the overall program authority and expert consultant for the design, integration, evaluation, and governance of BPA’s highly technical data analytics program, strategy, and end-to-end data lifecycle.
• Oversee and direct a team of 5–8 professional and administrative Federal employees (GS-13/14), including assigning work, evaluating performance, hiring, and addressing training or developmental needs.
• Allocate, manage, and account for organizational resources, including staff and funding, while establishing work plans, determining contractor use, and resolving budget shortages.
• Align data analytics efforts with executives across BPA, other federal partners, and external workgroups to promote modern data policies, practices, and technologies.
• Provide technical direction and leadership on the maintenance of the enterprise analytic platform and oversee complex data science analyses using advanced methodologies (e.g., machine learning, NLP, regression, and data visualization) to automate processes and unlock data-driven insights.

Requirements

• You must be a United States Citizen.
• This employer participates in the e-Verify program.
• Males must abide by Selective Service registration requirements.
• You will be required to report in person to the official duty location in Portland, OR.
• Selectee will be required to complete the Office of Government Ethics Standard of Confidential Financial Disclosure Report (OFGE450e) within 30 days of employment and annually.
• First-time supervisors will be required to serve a 1-year probationary period.

Qualifications

Basic Requirement: Degree in Mathematics, Statistics, Computer Science, Data Science, or a directly related field (at least at the baccalaureate level). OR a combination of education (30 semester hours in a qualifying major) and appropriate experience.

Specialized Experience: At least one year of specialized experience equivalent to the GS-13 level in the Federal service, defined as:

• Managing an enterprise data science program, including establishing strategic plans, formulating data policies, allocating resources, and coordinating initiatives with external partners.
• Advising executives on the governance and deployment of complex data science platforms and analytical infrastructure across the entire data lifecycle.
• Directing highly complex data science and machine learning projects using predictive modeling, natural language processing, and advanced statistics to automate business processes.

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

Education

This vacancy has a positive education requirement. You must provide copies of your college transcripts. Education must be obtained from an accredited institution recognized by the U.S. Department of Education. Foreign education must be reviewed by an organization recognized by the U.S. Department of Education.

Benefits

A career with the U.S. government provides employees with a comprehensive benefits package, including:

• Access to health, retirement, and other federal employee benefits.
• Work/life balance programs, such as telework options, flexible schedules, and wellness initiatives (e.g., BPA’s Be Well program supporting career, community, financial, physical, and social well-being).
• Hiring incentives may be authorized for highly qualified candidates based on budget availability and federal regulations.