Clarification from the agency

This position is being advertised under a Direct Hiring Authority.

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

• Leads projects through the innovation lifecycle from ideation through deployment in order to develop next generation advanced analytics capabilities in support of current and future audits, investigations, business operations, and other oversight challenges relevant to GAO’s mission. As necessary, the incumbent will work with experts outside GAO to determine leading practices for advanced analytics.

• Applies and combines diverse data science techniques including: Machine Learning, natural language processing, artificial intelligence, geospatial analyses, graph-based network modeling, advanced visualizations, descriptive statistics, and other statistical/mathematical/analytical methods to produce cohesive, user-centric solutions.
• Builds, optimizes, orchestrates, deploys, and tunes data science models and prototypes. Assesses disparate impacts, mitigates model biases, and evaluates relevant performance criteria, as applicable.
• Uses common data science tools, including scripted languages such as R, Python, SQL, and Java Scripts; Integrated Development Environment (IDE) and analytics platforms such as RStudio, SageMaker, RapidMiner, SAS, and Domino Data Lab; open-source solutions such as Kibana, Kubernetes, and elastic search; commercial off-the-shelf tools such as Informatica and Neo4j; and hardware-based capabilities such as Graphics Processing Units (GPU).
• Implements data quality considerations, including complex data processing, data quality assessment, data imputation, and data governance—including metadata as well as engineered features. Develops forensically sound, auditable, flexible, repeatable, and scalable extract transform and load (ETL) capabilities on a variety of structure and unstructured data.
• Uses cloud-based Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Software-as-a-Service (SaaS) capabilities to perform data science. Guides implementation and configuration of tools and other computational resources within established information security boundaries.
• Contributes to process development for and agile team culture of the Innovation Lab. Understands Generally Accepted Government Auditing Standards (GAGAS) and other relevant standards to advise GAO teams on best technical approaches to achieve quality results.
• Identifies deficiencies in problem statements, proposed approaches, and/or data access issues which are significant to the design, development, execution, and reporting out of advanced analytics pilots of the Innovation Lab.
• Supports the Assistant Director in developing, defining, and driving Innovation Lab strategy with regard to the exploration and deployment of advanced analytics techniques for improved or novel business outcomes.
• Supports Assistant Director in project management, acquisition project management, and stakeholder management. Incumbent may require certification as a level II COR, IT Project Manager, Scrum Master, or similar.
• Expands GAO’s advanced analytics and computational capabilities through a rigorous process of problem definition, ideation, review, revision, and execution to determine the most promising solutions and approaches which, if successful, could profoundly change the business of audit, investigations, and program evaluation for the future GAO.
• Performs other duties as assigned.

Conditions of employment

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

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-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.

You must meet all the requirements before the announcements closes. 

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):

• Knowledge of all of, and skill in applying three or more of, the following data science techniques:
  • 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.
• Skill in applying emerging theoretical methods to solve complex and previously unsolved data science problems.
• Ability to use cloud-based Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Software-as-a-Service (SaaS) capabilities for data science, which may include implementing and configuring tools and resources within established information security boundaries.
• Skill applying principles and methods with sufficient rigor to support activities under the Generally Accepted Government Auditing Standards (GAGAS) and Generally Accepted Accounting Principles (GAAP).
• Skill in selecting, organizing, and presenting appropriate information in a concise and balanced manner as well as skill in communicating such information to non-technical and technical target audiences alike.
• Ability to communicate well both in writing and orally, including preparing reports, participating in interviews and 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 and complete projects in a group setting, particularly across organizational boundaries and with those with less technical backgrounds.