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

Federal Deposit Insurance Corporation
This job announcement has closed

Summary

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.

Overview

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Job canceled
Open & closing dates
10/15/2024 to 01/10/2025
Salary
$109,243 to - $250,360 per year
Pay scale & grade
CG 12 - 14
Location
3 vacancies in the following location:
Washington, DC
Remote job
No
Telework eligible
Yes—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
14
Job family (Series)
Supervisory status
No
Security clearance
Other
Drug test
No
Position sensitivity and risk
Moderate Risk (MR)
Trust determination process
Announcement number
2024-DIR-DHB730
Control number
813958100

This job is open to

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Clarification from the agency

All United States Citizens. This is a Direct-Hire Public Notice.

Duties

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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.

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.

Minimum Background Investigation (MBI) 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:
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.).

Education

See requirements stated under QUALIFICATIONS.

Additional information

Selectee(s) for this position will be required to report to their duty station office two days per week.

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.

This vacancy announcement will have an initial open period of 60 days. Applicants MUST apply and/or update their applications by 11:59 pm ET at the close of the following cutoff dates to be considered: Cutoff date(s): 10/29/2024, 11/12/2024, 11/26/2024, 12/10/2024, 12/24/2024, 01/07/2025. Applications will be referred to the Hiring Official every two weeks during these dates. This announcement may be extended at the end of the initial 60-day open period. 

How you will be evaluated

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

This is a Direct-Hire Public Notice.  Applications will be accepted for the location identified in the public notice.  Veteran’s preference and traditional rating and ranking of applicants DO NOT apply to positions filled under this public notice. 

All complete applications (transcripts must be included, if applicable) will be verified for eligibility requirements and will be submitted to the hiring official upon request.

https://www.opm.gov/policy-data-oversight/hiring-information/direct-hire-authority/#url=Governmentwide-Authority

Upon the submission of your application package to USAJobs.gov, you will receive an automatic reply informing you that your application has been submitted, received and is being processed. If you provided an email address, you will receive an email message acknowledging the receipt of your application. Your application will remain active through the open period of this Public Notice. You will not receive any additional notifications, and your resume may not be reviewed for qualifications unless a position is requested to be filled by the hiring official. After you submit your application, you will be contacted only if further evaluation or interviews are required or upon your selection.”

If requested by Management, your application 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.

  1. Skill interpreting the results of AI/ML analytic techniques, including supervised, unsupervised, and reinforcement learning, and NLP, using statistical programs and programming languages (such as Python and R).
  2. Knowledge of the assumptions underlying AI/ML and NLP techniques and LLMs, and the limitations of these techniques.
  3. Knowledge of statistics, economics, and modeling, to analyze data pertaining to the operations and performance of financial institutions and the financial system.
  4. Knowledge of the tools and techniques for combining and analyzing datasets (including structured, semi-structured, unstructured, transactional, and survey data) in distributed or high-performance computing (HPC) environments (i.e., Spark, Greenplum, etc.).
  5. Ability to develop and implement automated solutions to analytical problems including the identification and on-boarding of relevant data sources; manipulation, and creation of derived metrics; identification and implementation of appropriate AI/ML, GIS and task automation methodologies; and visualization and communication of analytical results.
  6. Ability to organize, prioritize, and complete data analytic tasks.
  7. Ability to communicate analytic results, conclusions, and AI/ML, and NLP concepts
  8. Knowledge of communication and negotiation techniques to establish and maintain relationships within the Agency and Division as well as other Federal regulators, government agencies, and private sector organizations.

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


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