To qualify for this position, applicants must meet all requirements by the closing date of this announcement, 07/10/2026. Time-In-Grade Requirement: Applicants who are current Federal employees and have held a GS grade any time in the past 52 weeks must also meet time-in-grade requirements by the closing date of this announcement. For a GS-14 position you must have served 52 weeks at the GS-13. The grade may have been in any occupation, but must have been held in the Federal service. An SF-50 that shows your time-in-grade eligibility must be submitted with your application materials. If the most recent SF-50 has an effective date within the past year, it may not clearly demonstrate you possess one-year time-in-grade, as required by the announcement. In this instance, you must provide an additional SF-50 that clearly demonstrates one-year time-in-grade. Note: Time-In-Grade requirements also apply to some former Federal employees applying for reinstatement, as well as current employees applying for Veterans Employment Opportunities Act of 1998 (VEOA) appointment. See the Required Document section below for more information regarding the SF-50s needed to verify time-in-grade. You may qualify based on your experience as described below: Specialized Experience: You must have one year of specialized experience equivalent to at least the next lower grade GS-14 in the normal line of progression for the occupation in the organization. Examples of specialized experience would typically include, but are not limited to: Experience utilizing data mining and machine learning methods to extract meaningful insights and support advanced analysis across critical business functions. Executing data backup, recovery, and disposal procedures to maintain compliance with data governance and lifecycle requirements. Transforming raw data into meaningful information using data oriented programming languages and advanced visualization tools. Improving business processes by employing modern data science practices, including process analysis, data lifecycle management, and workflow modernization. Evidence of this specialized experience must be supported by detailed documentation of like duties performed in positions held on your resume. You will also need to provide work experience information such as hours per week, full-time/part-time status, and starting/ending dates of employment (month and year format) to establish you have one (1) full year of specialized experience at the required grade level. Quality Ranking Factor: Experience with data management related to the principles, procedures, and/or tools of data management, such as modeling techniques, data backup, data recovery, data dictionaries, data warehousing, data mining, data disposal, and data standardization processes. Must have experience with data science and modernizing and improving business processes 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; religions; spiritual; community; student; social). 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. Note: Resume must include job title and employer name, number of hours worked per week, start and end dates (including month and year), list of duties and responsibilities for each position held. In addition, if the experience was a federal position, you must list series and grade for each position held. Failure to include this information may result in an ineligible rating. A full year of work is considered to be 40 hours of work per week. Part-time experience will be credited on the basis of time actually spent in appropriate activities. Applicants wishing to receive credit for such experience must indicate clearly the nature of their duties and responsibilities in each position and the number of hours a week spent in such employment. Physical Requirements: Work is primarily sedentary, although some slight physical effort may be required. For more information on these qualification standards, please visit the United States Office of Personnel Management's website at http://://www.opm.gov/policy-data-oversight/classification-qualifications/general-schedule-qualification-standards/. The Interagency Career Transition Assistance Plan (ICTAP) and Career Transition Assistance Plan (CTAP) provide eligible displaced Federal/VA competitive service employees with selection priority over other candidates for competitive service vacancies. To be qualified you must submit appropriate documentation (a copy of the agency notice, your most recent performance rating, and your most recent SF-50 noting current position, grade level, and duty location) and be found well-qualified for this vacancy. To be found well qualified, applicants must meet the following qualifications: Demonstrated expertise in integrating diverse structured and unstructured data sources and applying advanced data modeling, warehousing, and dictionary standards to support enterprise-level analytics and decision frameworks. Led the design, development, and deployment of complex analytics solutions by applying data mining, natural language processing (NLP), and machine learning techniques to extract high-value insights from large-scale datasets. Executed end-to-end data lifecycle management-including data backup, recovery, disposal, and quality validation-to ensure data integrity, resiliency, and compliance with data governance protocols. Directed cross-functional data science initiatives by mentoring junior analysts, coordinating with internal and external stakeholders, and overseeing project execution from discovery to implementation. Developed and delivered executive-level visualizations and analytic products by synthesizing complex data trends, predictive model outputs, and performance metrics into actionable recommendations. Championed large-scale business process modernization and change management efforts by applying advanced data science methodologies to streamline workflows, drive adoption, and improve organizational performance. Information about ICTAP and CTAP eligibility is on OPM's Career Transition Resources website at http://www.opm.gov/policy-data-oversight/workforce-restructuring/employee-guide-to-career-transition/. Local Commuting Area: The local commuting area for this position is defined as a radius of 50 miles from Washington, D.C. This includes all locations that fall within a 50-mile driving distance from 810 Vermont Ave., NW, Washington, DC 20420.