Job Description:
Prescient Edge is seeking a SME-Computer Scientist (QAF Accreditation) to support a federal government client.
Please note that the availability of this position is contingent upon contract award.
SME-Computer Scientist (QAF Accreditation)
Description:
- Employs mathematics, statics, information science, artificial intelligence, machine learning, network science, probability modeling, data mining, data engineering, data warehousing, data compression, data protection, and/or other scientific techniques to correlate complex, technical findings into graphical, written, visual and verbal narrative products on trends of existing intelligence data to leverage other IC data sources.
- Develops and utilizes machine learning and data mining algorithms, prediction algorithms based on open-source capabilities.
- Integrates or codes algorithms to support Government intelligence search and discovery missions.
- Makes best practice recommendations on managing data within hardware, software, storage, and bandwidth constraints.
- Employs data science techniques to support predictive analysis, social media and crowd-source data analytics, wargaming, and strategy development.
- Employs exploratory analysis and rapid iteration techniques of large volumes of data to quickly derive intelligence.
- Prepares products to describe and document findings and activities.
Specific QAF duties:
- Review and evaluate QAF documentation submitted by Advanced Analytic (AA) owners to ensure compliance with tradecraft standards and adherence to best practices in AI System Development and Deployment.
- Assess QAF Documentation for completeness, accuracy, and thoroughness, and provide detailed feedback to AA owners and developers.
- Assist in maintaining a repository of QAF documentation to facilitate knowledge sharing and best practices across the organization.
- Provide consultation and guidance to AA owners, developers, and stakeholders on the QAF process, including best practices for AI system development, testing, and deployment.
- Collaborate with AA owners and developers to identify and address potential issues or gaps in QAF documentation.
- Develop and deliver training materials and workshops to educate AA owners, developers, and stakeholders on the QAF process and its application in AI System Development.
- Assist analytic methodologists and AA owners in translating technical documentation into analytic tradecraft compliant language.
- Collaborate with stakeholders to develop, implement, and refine best practices for translating technical documentation into tradecraft compliant language.
- Review and edit translated documentation to ensure accuracy, completeness, and adherence to tradecraft standards.
- Supports capability development by contributing, editing, and storing code in government owned/controlled source version control repositories.
Job Requirements:
Desired Experiences:
- Minimum 20 years of experience conducting analysis relevant to the specific labor category with at least a portion of the experience within the last 2 years.
Desired Education:
- Master's degree in an area related to the labor category from a college or university accredited by an agency recognized by the U.S. Department of Education.
Security Clearance:
- Security clearance required TS/SCI with CI POLY or the ability to obtain CI POLY.
Location:
- NCR to include Maryland and Virginia.
