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Form of workThis position is located in the Division of Resolutions and Receiverships, Washington DC or Dallas TX, of the Federal Deposit Insurance Corporation and provides support in the areas of AMM program financial modeling needs including big data management, probabilistic modeling, structured finance modeling, and data science techniques and provides reports, recommendations, and presentations to management.
Qualifications:Qualifying experience may be obtained in the private or public sector. 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, 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. Additional qualifications information can be found here.
Basic Requirements:
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 paragraph A above, plus additional education or appropriate experience.
Specialized Experience:
To qualify, applicants must have completed at least one year of specialized experience equivalent to at least the 12 grade level or above in the Federal service. Specialized experience is defined as experience in 1) designing or developing data analytics/science financial related products using techniques such as probabilistic modeling, structured finance modeling, machine learning, or artificial intelligence; or 2) conducting analysis using software and/or programming languages such as SQL, Python, R or Apache Spark to test hypotheses and predict outcomes; or 3) using data tools and techniques to process large datasets into structured formats for matching, analysis, or estimation.
See requirements stated under QUALIFICATIONS.
Employment Type: FULL_TIME
