Data Scientist (Data/AI Architect)

Interested candidates should be passionate about the ideals of our American republic, committed to upholding the rule of law and the U.S. Constitution, and committed to improving the efficiency of the Federal government. Hiring decisions will not be based on race, sex, color, religion, or national origin. Applicants must meet eligibility and qualification requirements by the closing date of this announcement. Time in grade restrictions do not apply to Direct Hire procedures.

QUALIFICATION REQUIREMENTS In order to be deemed as qualified candidates must meet all of the following criteria: education, specialized experience and the required competencies. Education-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 here plus additional education or appropriate experience. Transcripts must be submitted by the closing date of the announcement. If transcripts are not submitted, the application will be rated as ineligible.

Specialized Experience GS-13 Candidates must have one year of specialized experience which is equivalent to the GS-12 grade level in the Federal service. Specialized experience is defined as follows: 1. Designing and supporting complex, organization-wide data management, data governance, and/or data presentation architecture, including enterprise data catalogues, data warehouses, data lakes, or other data platforms; 2.

Developing and implementing artificial intelligence (AI) or machine learning (ML) tools to facilitate data discovery, enhance data analytics, and/or support data science programs with large, complex datasets; 3. Providing technical support in the use of advanced statistical, analytical, computational, or data science methods to identify trends, evaluate data quality, solve complex problems, and support organizational or policy decisions; 4.

Advising stakeholders on complex data, analytical, technical, or program issues and translating technical findings into clear recommendations for technical and non-technical audiences; and 5. Providing data subject matter expertise as part of multidisciplinary teams and projects involving data scientists, analysts, information technology professionals, project managers, contractors, or other technical and professional staff.

GS-14 Candidates must have one year of specialized experience which is equivalent to the GS-13 grade level in the Federal service. Specialized experience is defined as follows: 1. Designing and supporting complex, organization-wide data management, data governance, and/or data presentation architecture, including enterprise data catalogues, data warehouses, data lakes, or other data platforms; 2.

Managing development and implementation of artificial intelligence (AI) or machine learning (ML) tools to facilitate data discovery, enhance data analytics, and/or support data science programs with large, complex datasets; 3. Implementing data governance, data quality, validation, data management, or analytical standards and processes across organizational units; 4.

Providing technical support in the use of advanced statistical, analytical, computational, or data science methods to identify trends, evaluate data quality, solve complex problems, and support organizational or policy decisions; 5. Advising stakeholders on complex data, analytical, technical, or program issues and translating technical findings into clear recommendations for technical and non-technical audiences; and 6.

Providing data subject matter expertise as part of multidisciplinary teams and projects involving data scientists, analysts, information technology professionals, project managers, contractors, or other technical and professional staff. GS-15 Candidates must have one year of specialized experience which is equivalent to the GS-14 grade level in the Federal service. Specialized experience is defined as follows: 1.

Designing and supporting complex, organization-wide data management, data governance, and/or data presentation architecture, including enterprise data catalogues, data warehouses, data lakes, or other data platforms; 2. Leading the design, development, implementation, or improvement of enterprise data platforms, large-scale data collections, analytical systems, dashboards, data models, or automated reporting solutions; 3.

Managing development and implementation of artificial intelligence (AI) or machine learning (ML) tools to facilitate data discovery, enhance data analytics, and/or support data science programs with large, complex datasets; 4. Implementing data governance, data quality, validation, data management, or analytical standards and processes across organizational units; 5.

Providing technical leadership in the use of advanced statistical, analytical, computational, or data science methods to identify trends, evaluate data quality, solve complex problems, and support organizational or policy decisions; 6. Coordinating and supporting implementation of data architecture, data frameworks, and technological infrastructure supporting data collections and complex datasets, including those containing large-scale or nationwide geospatial data; 7.

Advising stakeholders on complex data, analytical, technical, or program issues and translating technical findings into clear recommendations for technical and non-technical audiences; and 8. Providing data subject matter expertise as part of multidisciplinary teams and projects involving data scientists, analysts, information technology professionals, project managers, contractors, or other technical and professional staff.

GS-13/14/15 COMPETENCIES Subject matter experts will review your application to determine if you meet the following required Knowledge, Skills and Abilities (KSA's): Ability to apply advanced data science, statistical, computational, geospatial, and analytical methods to large, complex, structured, and unstructured datasets to identify patterns, evaluate data quality, solve complex problems, and develop reliable findings that support organizational and policy decisions.

Skill supporting complex data programs, projects, and multidisciplinary teams involving data scientists, analysts, IT professionals, contractors, and other stakeholders. Ability to effectively establish priorities, allocate resources, resolve technical and programmatic problems, evaluate results, and ensure successful completion of major organizational initiatives.

Ability to communicate complex data management, data governance, data science, and other analytical and technical information clearly to managers, policymakers, attorneys, technical specialists, regulated entities, and other stakeholders; and in so doing, provide authoritative advice and recommendations that translate complex governance and analytical findings into understandable information supporting senior-level decision-making.

If you are deemed to be qualified by the Subject Matter Experts, your application will be referred to the hiring manager for hiring consideration. Alternatively, if your application is not deemed as qualified by the Subject Matter Experts, your application will not be referred to the hiring manager for hiring consideration.

As Data / AI Architect, the incumbent serves as a subject matter expert and advisor, using data science principles to support policymakers as team lead on an interdisciplinary team of data scientists, economists, statisticians, and other technical staff working on enterprise data management and data governance.

The Data Scientist has responsibility for (a) leading design and technical implementation of the enterprise data program, developing and documenting enterprise data architecture, standards, data models, data flows, and business intelligence, and supporting the development of enterprise data platforms; (b) providing Data Division leadership and other stakeholders in OEA and across the agency with data governance, data management, and artificial intelligence (AI) / machine learning (ML) policy guidance; (c) developing and using business intelligence tools, including advanced AI / ML tools, to effectively analyze data, create tables and visualizations, and develop insights from complex datasets; (d) supporting the implementation of enterprise data management and data collections from planning through availability of finalized data; and (e) providing analytic and technical support to Bureaus and Offices in the analysis of data.

The incumbent reports to Data Division managers and/or other OEA leadership on specific assignments, projects, and initiatives.