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Data Scientist

Legislative Branch
Government Accountability Office
This job announcement has closed

Summary

This position is located in GAO's Science, Technology Assessment, & Analytics (STAA) Team, Innovation Lab. The STAA is devoted to enhancing & expanding its support to Congress in conducting technology assessments, oversight of federal science and technology programs, & development of innovative analytical techniques in carrying out audits and evaluations.  The Innovation Lab aims to meet Congress's growing need to understand the science and technology of the future.  To learn more visit:  STAA

Overview

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Reviewing applications
Open & closing dates
09/01/2021 to 09/23/2021
Salary
$61,390 to - $102,136 per year
Pay scale & grade
PE 01
Location
FEW vacancies in the following location:
Washington, DC
Telework eligible
Yes—as determined by the agency policy.
Travel Required
Occasional travel - Some travel may be required.
Relocation expenses reimbursed
No
Appointment type
Permanent
Work schedule
Full-time
Service
Excepted
Promotion potential
NA
Supervisory status
No
Security clearance
Other
Drug test
No
Announcement number
GAO-21-STAA-801/1529-21DH
Control number
612820100

This job is open to

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Clarification from the agency

This position is being advertised under a Direct Hiring Authority. This is an entry-level, developmental position. You will participate in a Professional Development Program (PDP) that includes a combination of on-the-job and classroom training, and exposure to diverse projects within your assigned team.

Duties

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The STAA, Innovation Lab is seeking an experienced professional to serve as a Data Scientist to perform the following:

  1. Works on data science projects in support of GAO's mission.
  2. Applies theoretical knowledge to solve data science problems. If emerging technologies or new data science skills are needed, employee learns and implements them through training courses or on-the-job training.
  3. Uses data science techniques such as Machine Learning (ML), natural language processing (NLP), mathematics, statistics, algorithm development, geospatial analysis, graph-based network modeling, and data visualization to produce cohesive solutions.
  4. Identifies disparate impacts, model biases, and performance issues for models created by the Lab.
  5. Uses common data science tools such as scripted languages; Integrated Development Environment (IDE) and analytics platforms; data visualization tools; and automation tools.
  6. Develops well-documented and repeatable data extraction programs.
  7. Participates in agile team culture of the Innovation Lab.
  8. Identifies deficiencies in problem statements, proposed approaches, and/or data access issues for Innovation Lab projects.
  9. Supports Assistant Director and fellow Innovation Lab colleagues in project management and acquisition project management.
  10. Contributes to problem definition, review, revision, and execution of Innovation Lab projects.

Requirements

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Conditions of employment

  • Must be a U.S. Citizen.
  • Must be registered for Selective Service, if applicable. (www.sss.gov)
  • Completion of a financial disclosure statement is required.
  • Completion of a probationary period is required.
  • Must meet/maintain background and suitability requirements for employment.

This is an interdisciplinary, professional position which may be filled as an Engineer or Mathematical Statistician.

You must meet the education and specialized experience required by the position to be qualified.

Qualifications

In addition to the education requirement, you must have 1 year (52 weeks) of specialized experience at the next lower band or level equivalent to the GS-5 in the Federal Service, or comparable private/public sector experience which has equipped you with the skills and knowledge required to successfully perform the duties of the position. Specialized experience for this position is defined as:

  • Applying data science techniques using data science tools in academic or professional settings.
  • Applying at least three of the following in academic or professional settings:
    • Machine Learning (ML), including supervised, unsupervised, and adversarial;
    • Natural language processing (NLP), including sentiment classification and topic modeling;
    • Artificial Intelligence, including deep learning and robotics process automation (RPA);
    • Mathematical/statistical/analytical methods, including dimension reduction, entity resolution, rules-based queries, algorithm development, modeling, predictive analytics, descriptive statistics, sampling design, experimental design, and significance testing;
    • Extraction and processing methods for structured and unstructured data, including assessing data quality, imputation, applying governance, development of well-documented, flexible, repeatable, and scalable ETL routines across diverse data processing systems and data warehouses/lakes; and
    • Visualization, including descriptive charts and maps, geospatial analyses, and graph-based network modeling.
  • Using at least two data science tools or languages in an academic or professional setting. Examples include:
    • R, SAS, or STATA
    • Python and Jupyter
    • Tableau, Neo4J, or GIS
    • Matlab, Maple, Mathematica
    • SQL with relational databases

You must meet all the requirements before the announcements closes. 

Education

This position has a positive education requirement. You may qualify for this position based on one of the professional occupations below.

Documentation to verify your education MUST be submitted with your application in order to be considered.

General Engineering Series, 0801

You must meet one of the following:

  • Degree -- Engineering. To be acceptable, the program must: (1) lead to a bachelor’s degree in a school of engineering with at least one program accredited by ABET; or (2) include differential and integral calculus and courses (more advanced than first-year physics and chemistry) in five of the following seven areas of engineering science or physics: (a) statics, dynamics; (b) strength of materials (stress-strain relationships); (c) fluid mechanics, hydraulics; (d) thermodynamics; (e) electrical fields and circuits; (f) nature and properties of materials (relating particle and aggregate structure to properties); and (g) any other comparable area of fundamental engineering science or physics, such as optics, heat transfer, soil mechanics, or electronics.
  • Professional registration or licensure -- Current registration as an Engineer Intern (EI), Engineer in Training (EIT), or licensure as a Professional Engineer (PE) by any State, the District of Columbia, Guam, or Puerto Rico. You are eligible only for positions that are closely related to the specialty field of your registration.
  • Written Test -- Evidence of having successfully passed the Fundamentals of Engineering (FE) examination or any other written test required for professional registration by an engineering licensure board in the various states, the District of Columbia, Guam, and Puerto Rico.
  • Specified academic courses -- Successful completion of at least 60 semester hours of courses in the physical, mathematical, and engineering sciences and that included the courses specified in the basic requirements Degree. The courses must be fully acceptable toward meeting the requirements of an engineering program as described in Degree.
  • Related curriculum -- Successful completion of a curriculum leading to a bachelor's degree in an appropriate scientific field, e.g., engineering technology, physics, chemistry, architecture, computer science, mathematics, hydrology, or geology, AND at least 1 year of professional engineering experience acquired under professional engineering supervision and guidance.

Mathematical Statistics Series, 1529

You must meet one of the following:

  • Degree -- that included 24 semester hours of mathematics and statistics, of which at least 12 semester hours were in mathematics and 6 semester hours were in statistics.
  • Combination of education and experience -- at least 24 semester hours of mathematics and statistics, including at least 12 hours in mathematics and 6 hours in statistics, as shown in Degree, plus appropriate experience or additional education.

Additional information

This is a bargaining unit position.

Based on the staffing needs, additional selections may be made through this vacancy announcement.

You may be required to obtain and maintain a security clearance depending on the engagements, projects, and initiatives you are assigned to.

Travel and relocation expenses will not be paid for by the GAO.

You will be required to complete questions contained on the Declaration for Federal Employment (OF-306) at the time a tentative job offer is made. At the time of appointment, the selectee will be required to update the OF-306.

You will be subject to a determination of suitability for Federal employment.

GAO provides reasonable accommodations to applicants and employees with disabilities. To request accommodation, please email ReasonableAccommodation@gao.gov.

GAO's policy is to provide equal employment opportunity for all regardless of race, religion, color, sex (including pregnancy), national origin, age, disability, genetic information, sexual orientation, or gender identity.

GAO is part of the Legislative Branch of the Federal government. As such, all positions are in the excepted service. Initial appointments, permanent or indefinite, to the GAO require completion of a probationary period.

How you will be evaluated

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

The position(s) advertised in this announcement are covered by a direct hire authority. Traditional rating and ranking of applicants, including category rating, does not apply to this vacancy. Your qualifications will be initially evaluated against the basic qualifications only. Qualified applicants will be referred for consideration in accordance with the Office of Personnel Management Direct Hire guidelines. Veterans' Preference does not apply to positions covered by the direct hire authority.

Please make sure that your responses to the assessment questions are supported in your resume and follow all instructions carefully. If you provide incomplete answers, fail to provide a narrative response to any assessment question(s) that requires further explanation, or if your response to an assessment question is "see resume” or like answer, you may be determined ineligible.

All applicants will be evaluated based on their responses to the assessment questions, in conjunction with the following Knowledge, Skills and Abilities (KSA’s):

  • Professional knowledge of and skill in applying data science techniques such as:
    • Machine Learning (ML), including supervised, unsupervised, and adversarial;
    • Natural language processing (NLP), such as sentiment classification and topic modeling;
    • Artificial Intelligence, such as deep learning and robotics process automation (RPA);
    • Mathematical/statistical/analytical methods, such as dimension reduction, entity resolution, rules-based queries, algorithm development, modeling, predictive analytics, descriptive statistics, sampling design, experimental design, and significance testing;
    • Extraction and processing methods for structured and unstructured data, such as well-documented and repeatable extraction programs, assessing data quality, imputation, applying governance; and
    • Visualization, such as descriptive charts and maps, geospatial analyses, and graph-based network modeling.
  • Professional knowledge of and skill in applying principles, theories, concepts, and methodology sufficient to research, analyze, interpret, evaluate, and perform difficult, unprecedented assignments.
  • Ability to apply theoretical methods to solve data science problems.
  • Knowledge of cloud-based Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), or Software-as-a-Service (SaaS) capabilities.
  • Knowledge of data quality considerations, duplicates, missing data, keying errors, bias, imputation, and data governance.
  • Knowledge of model development, optimization, testing, and deployment.
  • Ability to organize, prepare, and present information in a concise and balanced manner.
  • Ability to communicate well both in writing and orally, including preparing reports, participating in meetings, and to making presentations. By way of definition, oral communication may include methods used by employees with disabilities such as sign language interpretation, text-to-speech or TTY technology, and amplification devices.
  • Ability to collaborate and work effectively to complete projects in a group setting.

To preview questions please click here.

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