Expert Computer Scientist - Quality Assurance Framework (QAF) Accreditation

Peraton•Herndon, VA

11d

About The Position

Peraton has an opportunity for you to join our military intelligence program (s) of record to deliver, operate and sustain modernized, transformed data science/ data analysis environments worldwide that enable speedy and precise decision making to warfighters . Responsibilities: Th e Expert Computer Scientist - Quality Assurance Framework (QAF) Accreditation utilizes expertise in designing, developing, and maintaining data systems and software to create and maintain these systems, develop new technologies and algorithms, and solve complex computing and data system problems . This position will focus on QAF Accreditation .

Requirements

Master’s degree in a relevant field, such as Computer Science , with a minimum of 20 years of work experience.
Expertise in algorithm development, data structures, and software development practices.
Strong analytical and critical thinking skills to interpret complex data and draw meaningful conclusions.
Experienced in utilization of the Quality Assurance Framework and standards.
Experience d in advanced analytics, machine learning, and data integration methodologies.
Experience d with intelligence databases, software, and analytical tools.
Ability to work collaboratively with users and stakeholders.
Capacity to adapt to changing situations to prioritize tasks effectively.
Excellent communication , analytical, and problem-solving skills.
This Position requires an Active TS/SCI and the ability to obtain a CI Poly, US Citizenship is required t o hold this clearance.

Nice To Haves

Doctorate degree in a relevant field , such as Computer Science .
Experience working in the customer environment is preferred.

Responsibilities

Employ 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 .
C orrelate complex, technical findings into graphical, written, visual and verbal narrative products .
Assess trends for existing data to identify and leverage other data sources .
Develop and utilize machine learning and data mining algorithms, including, but not limited to, Multiple Information Model Synthesis Architecture (MIMOSA) prediction algorithms based on open-source capabilities.
Integrate or code algorithms to support Government intelligence search and discovery missions.
Make best practice recommendations on managing data within hardware, software, storage, and bandwidth constraints.
Employ data science techniques to support predictive analysis, social media and crowd-source data analytics, wargaming, and strategy development.
Review and evaluation of QAF documentation submitted by a dvanced a nalytic product owners.
E nsure compliance with tradecraft standards and adherence to best practices in A rtificial I ntelligence (AI) system development and deployment.
Assess QAF documentation for completeness, accuracy, and thoroughness, and provide detailed feedback to advanced analytic product owners and developers.
Support maintaining a QAF documentation repository to facilitate knowledge sharing and best practices.
Collaborate with product owners and developers to identify and address potential issues or gaps in QAF documentation.
Develop and deliver training materials and workshops to educate advanced analytic product owners, developers, and stakeholders on the QAF process and its application in AI system development .
Assist analytic methodologists and advanced analytic product 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 .
Support capability development by contributing, editing, and storing code in Government owned/controlled source version control repositories.