This position is located in the Division of Insurance and Research, Center for Financial Research, and conducts and publishes research on the banking industry, bank regulation, financial markets, and deposit insurance. Additional selections may be made from this vacancy announcement to fill identical vacancies that occur subsequent to this announcement.  

Duties

Conducts analyses for complex data analysis projects, including projects that use leading-edge analytic approaches common to the field of data science, including the Artificial Intelligence and Machine Learning (AI/ML) techniques, Natural Language Processing (NLP) and Large Language Model (LLMs), statistical analysis, geographic analysis, data visualizations, and application/model development. Uses computational, statistical, and machine learning methods to conduct in-depth analyses and derive insights from large and complex data sources in multiple formats including structured, unstructured, semi-structured, transactional, and survey data using statistical software and/or programming languages. Develops custom computer program code to extract, combine, analyze, and interpret large and/or complex datasets to derive data-driven conclusions and solutions. Develops and maintains comprehensive, up-to-date knowledge of large, complex datasets related to the banking and financial system, including the uses and limitations of these datasets for a variety of different types of analyses.    Develops and maintains expertise in the efficient use of a variety of high-performance computing environments (including cloud platforms and technologies), statistical programming languages and software (such as Python, R, and SQL), and distributed computing software and databases (such as Apache Spark and Greenplum). Develops and maintains advanced proficiency in evolving Geographic Information System (GIS) analytic capabilities for using spatial data in analyses including the use of internal and external spatial data and GIS software (such as Google Maps API, ArcGIS, ArcPy, or QGIS). Clearly and concisely communicates analytic results, conclusions, and AI/ML concepts orally and in writing to technical and non-technical audiences both internally and externally. Participates in agency-wide and interagency forums covering data science, analytics, and other data-related topics.

Requirements

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 Requirement for CG-11: 1. 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 2. 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. AND  Specialized Experience: To qualify, applicants must have completed at least one year of specialized experience equivalent to at least the 9 grade level or above in the Federal service.  Specialized experience is defined as experience writing code in either Python or R to conduct economic, statistical, or machine-learning analyses. OR  By Substituting Education: Applicants must possess a Ph.D. or equivalent doctoral degree or 3 years of progressively higher level full-time graduate education leading to such a degree. Major field of study: mathematics, statistics, computer science, data science or field directly related to the position.  OR  By Combination of Education and Experience: A combination of graduate level education beyond the second full year of graduate level education, and specialized experience as described above, that together meet the qualification requirements for this position. Basic Requirement for CG-12: 1. 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 2. 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. AND  Specialized Experience: To qualify, applicants must have completed at least one year of specialized experience equivalent to at least the 11 grade level or above in the Federal service. Specialized experience is  defined as experience conducting economic, statistical, or machine-learning analyses by writing code in Python or R; and conducting economic, statistical, or machine-learning analyses using either unstructured data or Linux-based high-performance computing clusters or cloud platforms (such as AWS, Azure, Databricks, etc.). Basic Requirement for CG-13: 1. 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 2. 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. AND 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 is writing code in either Python or R to conduct machine learning analyses including using at least one of the following: neural networks, random forest, boosting, K nearest neighbors, support vector machines, K-means clustering, and Natural Language Processing. YOU MUST PROVIDE ALL TRANSCRIPT(S) (unofficial copy is acceptable).

Education

See requirements stated under QUALIFICATIONS.

Contacts

• Address Federal Deposit Insurance Corporation FDIC Human Resources Branch 25 Jessie Street at Ecker Square Suite 904 San Francisco, CA, California 94105 United States
• Name: Engelbert Espiritu
• Phone: 415-808-8182
• Email: [email protected]