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Summary This position is located in the Division of Insurance and Research of the Federal Deposit Insurance Corporation and provides information generated with advanced scientific tools, including mathematical, statistical, and econometric models and theories to make data-driven decisions regarding various aspects of the agency’s operations. Additional selections may be made from this vacancy announcement to fill identical vacancies that occur subsequent to this announcement. Responsibilities Provides technical leadership and serves as team lead on complex data analysis projects, including projects that use complex analytic approaches common to the field of data science including AI/ML techniques, Natural Language Processing (NLP), statistical analysis, geographic analysis, data visualizations, and application/model development. Conducts empirical studies and analyses using cutting-edge AI/ML techniques to analyze structured, semi-structured, or unstructured data to answer research and policy questions and inform FDIC decision-making. Identifies appropriate methods, processes, algorithms, and tools to estimate relevant models and interpret findings to answer research and analytic questions using varied structured and unstructured datasets. Develops and maintains expertise in the efficient use of a variety of cloud technologies (including Microsoft Azure Databricks and Apache Airflow), statistical programming languages and software (including Python and SQL), and distributed computing software and databases (such as Apache Spark and PySpark). Leads the development of auditable, flexible, repeatable, and scalable extract, transform, and load (ETL) or extract load transform (ELT) capabilities on large structured and unstructured data sources, including internal and external application programming interfaces (APIs). Utilizes software and/or programming languages to automate complex and intersecting data orchestration workflows. Leads the development of utilities or scripts to programmatically deploy and update data sources, and other analytic tools; and to automate task execution and the instantiation of data pipelines. Requirements Conditions of Employment Registration with the Selective Service. U.S. Citizenship is required. Employment Conditions. Completion of Financial Disclosure may be required. Background Investigation (BI) required 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: 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 above, plus additional education or appropriate experience. YOU MUST PROVIDE YOUR TRANSCRIPT(S) (unofficial copy is acceptable) In addition to the Basic Requirement, listed above, Applicant must also meet the following Specialized Experience: To qualify, applicants must have completed at least one year of specialized experience equivalent to at least the 14 grade level or above in the Federal service. Specialized experience is defined as experience in at least three of the following areas: (1) conducting 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; (2) performing Natural Language Processing using at least one of the following: transformer models (such as BERT) or local large language models; (3) conducting analyses using large datasets with millions of observations; and (4) writing code to conduct economic or statistical or machine-learning analyses using at least one of the following languages or technologies: Python, R, or Spark. Education See requirements stated under QUALIFICATIONS. Additional Information Selectee(s) for this position will be required to report to their duty station office at least 1 day per pay period beginning January 2, 2024, and at their supervisor’s direction to support mission and project needs. In person reporting requirements are expected to increase in July 2024. Salary reflects a pay cap for this position of $252,500 If selected, you may be required to serve a probationary period. To read about your rights and responsibilities as an applicant for Federal employment, click here.