Supervisory Data Scientist

About the Position - Portland This position is located in Portland, OR which boasts huge spans of amazing trees, foliage, landscape, and everywhere you look you can appreciate beautiful greenery!

It is known as the most bike-friendly city in America, has a train system that greets you at the airport spanning across the city, and is home to the Portland International Rose Garden, the oldest in the country!

Portland is the one place where you will find lively festivals, energetic music, mouthwatering food, and for you basketball fans, the Portland Trail Blazers are a 7 minute walk from the HQs building! There is always something new to experience in this eco-friendly town!

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 overall Bonneville 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 data life cycle end-to-end.

Oversee and direct a team of 5-8 professional and administrative Federal employees (GS-13/14), which includes 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 the use of contractors, and resolving budget shortages.

Align data analytics efforts with executives across BPA, other federal partners, and external workgroups to promote the adoption of 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.

BASIC REQUIREMENT: A. 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 - B.

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.

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: 1) Experience managing an enterprise data science program, including establishing strategic plans, formulating data policies, allocating resources, and coordinating initiatives with external partners; 2) Experience advising executives on the governance and deployment of complex data science platforms and analytical infrastructure across the entire data life cycle; and 3) Experience directing highly complex data science and machine learning projects using predictive modeling, natural language processing, and advanced statistics to automate business processes.

"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 meet all of the requirements as described in this section.

You must meet all qualifications and eligibility requirements by the closing date of this announcement.