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

Duties

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

Requirements

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-12 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 at least three of the following advanced data science techniques in a professional setting: 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 languages and at least two data science tools in a professional setting. Examples include: R, SAS, or STATA Python and Jupyter Tableau, Neo4J, or GIS Matlab, Maple, Mathematica SQL with relational databases Developing automation that reduced burden, increased efficiency, reduced errors, or increased productivity. Using agile techniques to manage data science projects. Communicating technical information to non-technical audiences. 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. You must meet all requirements before the closing date of the announcement.

Education

This is an interdisciplinary, professional position which may be filled as an Engineer or Mathematical Statistician. Documentation to verify your education MUST be submitted with your application in order to be considered.

This position has a positive education requirement. To qualify you must meet the requirements for either occupational series listed below.

General Engineering Series, 0800 (includes 801)

A. Degree: Successful completion of a professional engineering degree. To be acceptable, the program must: (1) lead to a bachelor's degree (or higher) in a school of engineering with at least one program accredited by the Accreditation Board for Engineering and Technology (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. Such education must demonstrate the knowledge, skills, and abilities necessary to do the work of the position.

OR

B. Combination of education and experience -- college-level education, training, and/or technical experience that furnished (1) a thorough knowledge of the physical and mathematical sciences underlying engineering, and (2) a good understanding, both theoretical and practical, of the engineering sciences and techniques and their applications to one of the branches of engineering. The adequacy of such background must be demonstrated by one of the following:

1. 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. Absent other means of qualifying under this standard, those applicants who achieved such registration by means other than written test (e.g., State grandfather or eminence provisions) are eligible only for positions that are within or closely related to the specialty field of their registration For more information about EI and EIT registration requirements, please visit the National Society of Professional Engineers website at: http://www.nspe.org
2. 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 The FE examination is not administered by the U. S. Office of Personnel Management. For more information, please visit: http://www.nspe.org/Licensure/HowtoGetLicensed/index.html.
3. Specified academic course - Successful completion of at least 60 semester hours of courses in the physical, mathematical, and engineering sciences and in engineering that included the courses specified in the basic requirements under paragraph A (above). The courses must be fully acceptable toward meeting the requirements of an engineering program as described in paragraph A (above)
4. Related curriculum - Successful completion of a curriculum leading to a bachelor's degree in am appropriate scientific field, e.g., engineering technology, physics, chemistry, architecture, computer science, mathematics, hydrology, or geology, may be accepted in lieu of bachelor's degree in engineering, provided the applicant has had at the least 1 year of a professional engineering acquired under professional engineering supervision and guidance. Ordinarily there should be either an established plan of extensive training to develop professional engineering competence, or several years of prior professional engineering -type experience, e.g., in interdisciplinary positions. (The above examples of related curricula are not all inclusive.)

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; OR
• 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.

Contacts

• Address Government Accountability Office Human Capital Office 441 G Street NW Washington, DC 20548 US
• Name: Ebonye Watson
• Email: [email protected]