As a Data Scientist, you will derive insights from artificial intelligence, machine learning, and natural language processing to help ensure that the federal banking system is safe, sound, and fair. You will analyze data sets, use predictive analytics to identify emerging risks in the federal banking system, and work with bank examiners to enhance existing processes for bank supervision. Supervision Risk and Analysis Systemic Risk Identification and Support Supervision Analysis Washington, DC

Duties

As a Data Scientist, you will: Apply data science approaches, systems, applications, and analytical tools including data management, statistical and reporting methodologies and tools, text analytics, machine learning/artificial intelligence (AI/ML) models, data visualizations, and others to perform assignments. Conduct analyses with open source (e.g., Python) and commercial products (e.g., Alteryx, AWS tools), identifying appropriate packages and tools. Extract data from multiple sources and combine them to discover patterns, test hypotheses, and make predictions that inform operational and bank supervision decisions. Use a variety of statistical programming languages and database software (such as SAS, R, Python, JavaScript, Alteryx and SQL) as well as other quantitative analysis tools and techniques such as machine learning/artificial intelligence (AI/ML) models/tools and text analytics tools. Write computer programs and code, develop dashboards, spreadsheets, reports, screens, and spatial analysis such as maps and regressions. Advise and consult on the potential benefits/uses of automation to improve the efficiency of program operations. Participate in the design of presentations and interpretations of analytical outputs tailored to specific audiences that includes interactivity and narrative storytelling where appropriate and translate concepts, findings, and limitations into concise, plain language.

Requirements

Qualifications

You must meet the following requirements within 30 calendar days after the closing date of this announcement: To qualify for the NB-IV level, applicants must have specialized experience equivalent to the next lower level, NB-III or GS-07 level in the federal service. This experience may have been gained in either the public or private sector. One year of experience refers to full-time work; part-time work is considered on a prorated basis. Examples of specialized experience for this position include: Experience using coding languages (e.g., SQL, Python, JavaScript, R, SAS) to conduct analysis, OR Experience using modeling applications to create forecasting models. OR You may substitute education for experience as follows: 2 years of progressively higher-level graduate education leading to a master's degree or master's or equivalent graduate degree or above. OR You may qualify by a combination of experience and education.Only education in excess of 1 year of graduate education is creditable toward meeting the specialized experience requirement. One year of full-time graduate education is considered to be the number of credit hours that the school attended has determined to represent 1 year of full-time study. If that number cannot be obtained from the school, 18 semester hours should be considered an academic year of graduate study. IN ADDITION: Applicants must also meet the individual occupational 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. The experience may have been gained in the public sector, private sector, or through volunteer service. One year of experience refers to full-time work; part-time work is considered on a prorated basis. To receive any credit for your work experience, please indicate dates of employment by month/year, and indicate the number of hours worked per week, on your resume.

Education

Please see Qualifications section for education.

Contacts

• Address Supervision Risk and Analysis 400 7th Street SW Washington, DC 20219 US
• Name: Tyler Bruce
• Phone: 202-649-6665
• Email: [email protected]