Data Scientist, 1560-CG-12/13/14 - Military Veterans

This position is located in the Division of Insurance and Research, Research & Regulatory Analysis Branch of the Federal Deposit Insurance Corporation and support multiple sections in the Center for Financial Research (CFR) in the Division of Insurance and Research. Additional selections may be made from this vacancy announcement to fill identical vacancies that occur subsequent to this announcement.

At the full performance level, major duties include: 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). Communicates analytic results, conclusions, and AI/ML concepts 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.

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: A. 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 B. 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. In addition to meeting the Basic Requirement above, applicants must also meet the minimum qualifications listed below to be considered: CG-12 - To qualify at this level, Applicant must have completed at least one year of specialized experience equivalent to at least the CG/GS-11 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 (e.g. AWS, Azure, Databricks, etc.). CG-13 - To qualify at this level, Applicant must have completed at least one year of specialized experience equivalent to at least the CG/GS 12 level or above in the Federal service. Specialized experience is defined as experience 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. CG-14 - To qualify at this level, Applicant must have completed at least one year of specialized experience equivalent to at least the CG/GS-13 level or above in the Federal service. Specialized experience is defined as experience in writing code in Python or R to conduct analyses using machine learning algorithms including at least one of the following: neural networks, random forest, boosting, Naïve Bayes, K nearest neighbors, support vector machines, or K-means clustering and either performing Natural Language Processing using at least one of the following: transformer models (e.g. BERT) or local large language models; or conducting analyses using Linux-based high-performance computing clusters or cloud platforms (e.g. AWS, Azure, Databricks, etc.).

Registration with the Selective Service. U.S. Citizenship is required. Employment Conditions. Completion of Financial Disclosure may be required. Minimum Background Investigation (MBI) required.