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Celestar · 1 month ago

Senior Statistician/Mathematician (QAF Accreditation) - OBIQUA

Reston, VA

Full-time

Onsite

Senior Level, Lead/Staff

12+ years exp

Celestar Corporation is seeking a Senior Statistician/Mathematician to support The Defense Intelligence Agency (DIA) under the Object Based Intelligence and Quality Assurance (OBIQUA) task order. The role involves applying mathematical theories and statistical methods to solve intelligence problems and develop models for analysis, while also providing guidance on quality assurance processes.

ConsultingFinancial ServicesHuman Resources

No H1B

Security Clearance Required

Responsibilities

This opportunity will support multiple DIA initiatives, including the Machine-Assisted Rapid-Repository System (MARS), Object Management Services (OMS), and Object-Based Intelligence (OBI)

The Statistician/Mathematician, Quality Assurance Framework (QAF)

Develops and applies fundamental mathematics, mathematical or statistical theory to collect, organize, interpret and summarize numerical data to generate usable information to solve a wide range of intelligence problems

Applies mathematical theories and statistical methods to solve practical problems

Develops mathematical or statistical models of phenomena for analysis or computational simulation

Designs complex metrics projects that apply valid scientific techniques and utilize information obtained from baselines or historical data to structure analyses

Plans and performs data collection for projects, determining types/sizes of sample groups and prepares data for processing by organizing information and checking for inaccuracies

Processes large amounts of data for statistical modeling and graphic analysis (metrics)

Develops computer code to automate the collecting and processing of data

Produces results of analyses in graphs, charts, tables, and metrics. Prepares products to describe and document findings and activities

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 developer

Assist in maintaining QAF repository of 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

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

Develop and apply statistical models and methods to evaluate AI system performance, robustness, and fairness in all source analysis contexts

Collaborate with the Computer Scientist to develop and implement testing methodologies for AI system validation and evaluation

Analyze and interpret results of statistical models and methods to inform AI system development and improvement

Supports capability development by contributing, editing, and storing code in Government owned/controlled source version control repositories

Qualification

Statistical modelingMathematical theoryData analysisAI system evaluationQAF documentationTraining developmentIndependent workCollaboration

Required

Minimum 12 years of experience related to the specific labor category with at least a portion of the experience within the last 2 years with a master's degree

A minimum of 17 years of experience related to the specific labor category with at least a portion of the experience within the last 2 years with a bachelor's degree

Demonstrates ability to work independently and with minimal oversight