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Data Scientist, CG-1560-15

Federal Deposit Insurance Corporation
This job announcement has closed

Summary

This position is located in the Division of Insurance and Research, Financial Modeling and Research Section and provides support in the areas of data science and complex analytics, including the use of machine learning and artificial intelligence techniques to support the mission of the Division and the Corporation.

Additional selections may be made from this vacancy announcement to fill identical vacancies that occur subsequent to this announcement.

Overview

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Reviewing applications
Open & closing dates
09/21/2023 to 10/05/2023
Salary
$170,779 to - $250,000 per year
Pay scale & grade
CG 15
Location
Washington, DC
1 vacancy
Remote job
No
Telework eligible
Yes—The FDIC offers position-specific telework options. Please see the Additional Information section below for more information on telework options. Telework options are subject to change.
Travel Required
Occasional travel - Occasional travel may be required.
Relocation expenses reimbursed
Yes—Relocation benefits may be provided in accordance with FDIC policy.
Appointment type
Permanent
Work schedule
Full-time
Service
Competitive
Promotion potential
15
Job family (Series)
Supervisory status
No
Security clearance
Other
Drug test
No
Position sensitivity and risk
High Risk (HR)
Trust determination process
Announcement number
2023-HQD-B0513
Control number
750495100

This job is open to

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Clarification from the agency

All United States Citizens. Applicants with status or those eligible under special hiring authorities, should apply under FDIC merit promotion announcement 2023-HQ-B0588 . However, if you desire consideration also under this public non-status announcement, you must apply to both. Status applicants are current permanent Federal employees in the competitive service and former Federal employees with reinstatement eligibility.

Duties

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  • Conducts empirical studies and analyses using AI/ML techniques to analyze structured, semi-structured, or unstructured data.
  • Identifies methods, processes, algorithms, tools, and systems to generate and interpret findings from varied structured and unstructured datasets.
  • Develops algorithms and tools for data manipulation and processing, as well as the use of data visualization techniques.
  • Develops and maintains expertise in the efficient use 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).
  • Provides technical leadership and serves as team lead on 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.
  • Leads in the development of applications and visualizations of geographic data for analyses of climate and other risks; demonstrates proficiency in evolving Geographical Information System (GIS) mapping capabilities, including internal and external geographic datasets and mapping software (such as Google Maps API or ArcGIS).
  • Translates concepts, findings, and results into concise, plain language; closely ties conclusions to the agency mission, original problem statement, and team objectives

Requirements

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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 Requirements:

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.

In addition to the basic requirements stated above, applicants must also possess specialized experience.

To qualify, applicants must have completed at least one year of specialized experience equivalent to at least the GS/CG-14 grade level or above in the Federal service. Specialized experience is experience that includes: (1) conducting analyses using machine learning algorithms including at least one of the following: neural networks, random forest, boosting, K nearest neighbors, support vector machines, K-means clustering, and Natural Language Processing; (2) conducting analyses using large datasets, such as financial, economic, climate and/or geographic datasets; and (3) writing code to conduct analyses using at least two of the following languages or statistical software or technologies: Python, R, SAS, Stata, Julia, Matlab, Octave, or Spark.
Applicants eligible for ICTAP (Interagency Career Transition Assistance Program) must achieve a score of 80 or higher in the online assessment to be determined “well qualified” for this position. For more information, click here.

Education

See requirements stated under QUALIFICATIONS.

Additional information

Selectee(s) for this position will be required to report to their duty station office 3 days per week beginning January 1, 2024. 

To read about your rights and responsibilities as an applicant for Federal employment, click here.

If selected, you may be required to serve a probationary period.

Salary reflects a pay cap for this position of $250,000.

How you will be evaluated

You will be evaluated for this job based on how well you meet the qualifications above.

Your resume and the online assessment questionnaire will be reviewed to determine whether you meet the qualification requirements outlined in this announcement. Therefore, it is imperative that your resume contain sufficiently detailed information upon which to make the qualification determination. Please ensure that your resume contains specific information such as position titles, beginning and ending dates of employment for each position, average number of hours worked per week, and if the position is/was in the Federal government, you should provide the position series and grade level.

Your resume will also be evaluated to measure your responses to the assessment questions. If you rated yourself higher on the questionnaire than what is supported by your resume, your overall qualifications assessment may be adversely affected.

If you are found qualified, you will be placed in one of three categories: Best Qualified, Highly Qualified, or Qualified. These category assignments are a measure of the degree in which your background and responses to the assessment questions match the competencies/knowledge, skills, and abilities (KSAs) listed below. Within these categories, candidates eligible for veterans’ preference will receive selection priority over non-veterans.

  1. Skilled in the application and interpretation of AI/ML analytical techniques including supervised, unsupervised and reinforcement learning, or NLP, utilizing statistical programs and programming languages (such as Python, R, SAS, etc.).

  2. Knowledge of the assumptions underlying AI/ML techniques and the limitations of these techniques. 
  3. Ability to identify and implement AI/ML, GIS and task automation methodologies.

  4. Ability to utilize data visualization tools (such as R or Python, Microsoft Power BI, GIS software) to communicate and display analytical results including the development of graphics, charts, and other visualizations.

  5. Knowledge of statistics, econometric modeling, and quantitative financial analysis.

  6. Skill applying evaluation methods of data pertaining to the performance of financial institutions and the financial system as a whole, including the identification and measurement of systemic risk.
  7. Ability to lead the development and implementation of automated solutions to analytical problems including the identification and on-boarding of data sources; manipulation, and creation of derived metrics; identification and implementation of AI/ML, GIS and task automation methodologies; and visualization and communication of analytical results.

  8. Ability to design visualizations tailored to specific audiences (i.e., analysts, economists, examination or resolution staff, and senior management).
  9. Ability to organize, prioritize, and complete multiple tasks while coordinating the efforts of multiple supporting staff with limited direct supervision.

  10. Ability to combine large volumes of geographic, demographic, census, climate, and survey data for map-based analytical use cases.
  11. Ability to lead in the identification, ingestion, and analysis of data to inform climate-related risk modeling, inter-agency research and outreach.

You do not need to respond separately to these KSAs. Your answers to the online questionnaire and resume will serve as responses to the KSAs. 


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