Data Scientist

The duties may include, but are not limited to

Key contributions involve solving technical issues, such as designing data flows and using data systems to create new and modify existing tools for better customer experience.

Conducts statistical analyses and applies data science methods to support the transition to data-driven initiatives.

Creates interactive data visualization tools like Tableau, ESRI, R, Python, and Power BI to present analytical results with graphs, charts, dashboards, and other visualizations.

Follows all data governance, including standards, policies, and procedures and documentation to meet established requirements.

Offers management technical guidance and recommendations.

Communicates clearly and professionally with subject matter experts (SME), analysts, other data professionals, and stakeholders

Identifies problems, determines solutions, tests hypotheses, and evaluates results.

Works collaboratively with program and management staff to analyze issues, make and implement recommendations, achieve consensus, and deliver informed advice.

Performs other duties as assigned.

Applicants must meet all qualifications and eligibility requirements by the closing date of the announcement, including specialized experience and/or education, as defined below. 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 the paragraph above, plus additional education or appropriate experience.

In addition to the basic requirement applicants must also possess: FOR THE GS-13 LEVEL: Applicants must have one year of specialized experience (equivalent to the GS-12 level) that may have been obtained in the private or public (local, county, state, Federal) sectors which demonstrates: Leading complex data science projects from design through deployment by applying analytical methods such as statistics or machine learning, maintaining high data quality, and coordinating with cross-functional teams to meet organizational needs.

Building and maintaining large-scale automated workflows to process, manage, and validate complex datasets. Cataloging, documenting, and standardizing datasets and workflows to improve accessibility, discoverability, and reuse. Clearly communicating analytical work to executives, technical staff, and non-technical stakeholders.

Note: There is no education substitution for this grade level. TRANSCRIPTS are required if: This position requires specific coursework or a degree in a specific field to be basically qualified. This education must have been successfully completed and obtained from an accredited school, college, or university.

Experience refers to paid and unpaid experience, including volunteer work done through National Service programs (e.g., Peace Corps, AmeriCorps) and other organizations (e.g., professional, philanthropic, religious, spiritual, community, student, social).

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