Data Analyst (AI Assurance Lead)
What you'd do
Data Analysts combine mission and business analytics knowledge and a consultative approach to prepare reports, briefings, and communicate recommendations to enable stakeholder decision making. Data analysts identify, collect, structure, and evaluate data from various sources to meet analytic needs and prepare data for analysis using a range of data and visualization tools in alignment with data go
Major duties
ADDITIONAL INFORMATION: The National Geospatial-Intelligence Agency (NGA) serves as the world leader in providing timely, relevant, accurate and actionable geospatial intelligence (GEOINT). NGA's civilian, military and contract personnel evaluate imagery, maps, charts, multiple layers of foundation data - such as terrain, elevation and gravity - and the full spectrum of visible and invisible light in order to help users visualize what is happening at a particular place and time. Our intelligence officers go beyond describing "what, where and when" to revealing "how and why". Our work enables decision advantage for our policymakers, warfighters, intelligence professionals and first responders. Additional Application Requirement: You may be asked to complete one or more assessments in addition to the application you submit on this website as part of your application to NGA. These assessments may include but are not limited to online questionnaires or assessments that require you to describe your job-related knowledge, skills, abilities, or other characteristics that are aligned with the mandatory and desirable qualifications of this job posting. The information you provide in the application you submit must support the response you provide to this questionnaire. You will receive an email to describe any additional assessments required. Please monitor your emails and complete any required assessments as soon as possible.
What you need to qualify
MANDATORY QUALIFICATION CRITERIA: For this particular job, applicants must meet all competencies reflected under the Mandatory Qualification Criteria to include education (if required). Online resumes must demonstrate qualification by providing specific examples and associated results, in response to the announcement's mandatory criteria specified in this vacancy announcement: 1. Demonstrated experience evaluating AI systems by executing standardized benchmarking protocols on AI platforms (e.g., Gemini Pro; GPT-4, Claude, or Llama-based frameworks). 2. Demonstrated experience scaling AI capabilities by transitioning enterprise-level automation platforms, from testing environments to live production. 3. Demonstrated experience auditing AI models by either formal vulnerability or bias assessments on AI services (e.g., Retrieval-Augmented Generation (RAG) systems; autonomous agents, or multimodal image/audio classifiers) prior to operational deployment. EDUCATION REQUIREMENT: A. Education: Bachelor's degree from an accredited college or university in Data Analytics, Business Intelligence, Mathematics, Statistics, Actuarial Science, Computer Science, Engineering, Information Design, Operations Research, Finance, Information Technology, or a related field. -OR- B. Combination of Education and Experience: A minimum of 24 semester (36 quarter) hours of coursework in any area listed in option A, plus experience that requires the application of tools and algorithms to identify trends and patterns in data, or in a related area that demonstrates the ability to successfully perform the duties associated with this work. As a rule, every 30 semester (45 quarter) hours of coursework is equivalent to one year of experience. Candidates should show that their combination of education and experience totals 4 years. DESIRABLE QUALIFICATION CRITERIA: In addition to the mandatory qualifications, experience in the following is desired: 1. Demonstrated experience evaluating technical architectures by assessing system dependencies, model documentation, or implementation plans in support of enterprise adoption decisions. 2. Demonstrated experience utilizing secure enterprise infrastructure by deploying or integrating AI models within large-scale, highly regulated environments (e.g., IC Foundational AI Stack, AWS GovCloud, or financial/commercial equivalents). 3. Demonstrated experience building AI capabilities by designing or scaling operational AI or automation platforms, resulting in measurable improvements to business workflows, mission effectiveness, or operational efficiency. 4. Demonstrated experience overseeing technical vendors through technical execution management, contractor oversight, or procurement processes for AI or software contracts (e.g., serving as a Contracting Officer's Representative (COR), Technical Monitor, or commercial Vendor Manager). 5. Demonstrated experience validating AI data pipelines by assuring the quality of input datasets for model training, fine-tuning, or performance testing initiatives.
Before you apply
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