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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.
GAO is seeking an experienced data scientist professional that:
- Works on data science projects in support of GAO’s mission.
- 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.
- 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.
- Identifies disparate impacts, model biases, and performance issues for models created by the Lab.
- Uses common data science tools such as scripted languages; Integrated Development Environment (IDE) and analytics platforms; data visualization tools; and automation tools.
- Develops well-documented and repeatable data extraction programs.
- Participates in agile team culture of the Innovation Lab.
- Identifies deficiencies in problem statements, proposed approaches, and/or data access issues for Innovation Lab projects.
- Supports Assistant Director and fellow Innovation Lab colleagues in project management and acquisition project management.
- Contributes to problem definition, review, revision, and execution of Innovation Lab projects.
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.
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.