Celestar Corporation is seeking a Junior-level Data Scientist (OBI Analytic Efficiency Enablement) to support The Defense Intelligence Agency (DIA) under the Object Based Intelligence and Quality Assurance (OBIQUA) task order. The primary place of performance will be at DIA Facilities across the National Capital Region (NCR). If interested and meet the qualifications, we encourage you to apply for this rewarding and impactful opportunity.
ANTICIPATED AWARD: TBD
ANTICIPATED START: TBD
PERIOD OF PERFORMANCE: 1 Base Year + 4 Option Years
LOCATION: DIA Facilities across the National Capital Region (NCR)
CLEARANCE REQUIREMENT: Active TS/SCI with a Current CI Poly
About Us:
Celestar, a proud Veteran-Owned company, offers highly competitive salaries and benefits. Our comprehensive benefits package includes company-paid employee and family dental insurance, employee health insurance, life insurance, and disability coverage. Additionally, we provide a 401(k)-retirement plan with company matching, paid holidays, and personal time off.
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 Data Scientist (OBI Analytic Efficiency Enablement) Conducts data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis, and uses scientific techniques to correlate data into graphical, written, visual and verbal narrative products, enabling more informed analytic decisions.
- Proactively retrieves information from various sources, analyzes it for better understanding about the data set, and builds AI tools that automate certain processes.
- Duties typically include: creating various ML-based tools or processes, such as recommendation engines or automated lead scoring systems. Performs statistical analysis, applies data mining techniques, and builds high quality prediction systems.
- Should be skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI-) and Tableau; major data science languages, such as R and Python; managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms.
- Should have prior experience with large data multi INT analytics, ML, and automated predictive analytics.
- Possesses a professional or graduate certificate in data science from a university, major online learning platform (all business for Data Scientists at any experience level).
- Designs, develops, and evaluates leading-edge algorithmic intelligence concepts, practices, and technologies for implementation into OBI via all-source analysis tradecraft, assessments, production, and dissemination.
- Proposes advanced statistical or mathematical techniques and methodology that may permit identification and evaluation of alternatives, assists in model formulation or experimental test design, and shares jointly in team responsibility for development of advanced analytic techniques and assessments.
- Collaborate with team members to develop and refine exploratory efforts leveraging novel technologies (e.g. large language models, natural language processing, machine learning) to automate ontologies and associated components to ensure semantic accuracy, relevance, and interoperability with existing knowledge modeling and knowledge graph capabilities.
- Evaluates data science, artificial intelligence, and other advanced analytic methods for risks, biases, and limitations that would distort conclusions.
- Collaborate with team members to develop and refine semantic data retrieval and reasoning across knowledge graphs through development and optimization of data queries via multiple protocols (e.g. GraphQL, SPARQL, SHACL, SQL).
- Conducts continuous independent research on methods of analysis in government, industry, and academia to keep abreast of the state of the art, keeps senior leadership apprised of the advances and applicability to programs.
- Utilizes in-depth knowledge of relevant theories, techniques, procedures and processes to investigate, prototype, and evaluate technologies to improve all-source intelligence analysis.
- Collaborate with team members to develop and refine exploratory efforts leveraging novel technologies (e.g. large language models, natural language processing, machine learning) to support and automate entity recognition and extraction, summarization, in accordance with analytic tradecraft standards, to enhance advanced analytic integration for OBI efforts.
- Performs research studies to understand the process of augmenting or automating all source analytic processes using various computer models.
- Provides incremental enhancements to tools, capabilities, processes, and methods.
- Possesses in-depth knowledge and experience in using data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis, and scientific techniques to correlate data into graphical, written, visual and verbal narrative products, enabling more informed analytic decisions.
- Writes either R or Python scripts to drive data science workflows, have experience using SQL, and managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms.
- Possesses prior experience with large data, spatial data, Multi-INT analytics, ML, and automated predictive analytics.
- Works with ambiguous information, deconstruct key questions, leverage spatial data, exploit application programming interfaces, suggest methodologies, develop data schemas to structure observations. This requires working knowledge of coding and scripting, information science, mathematics, machine learning, visual analytic modeling tools, and relevant Standard Operating Procedures (SOPs) to create repeatable, widely applicable procedures to support all-source intelligence analysis and production.
- Creates and works in distributed analytic environments, scaling algorithms to work on increasingly large and complex datasets that are larger than RAM.
- Serves as the primary POC for data science expertise, ensuring tradecraft compliance and analytic standards as it relates to data science techniques on the contract.
- Provides advice on emerging data science methods, tools, algorithms, training, or requirements to advance DIA's analytic edge in its use of data science.
- Works with DIA vendors and the software developers to implement distributed algorithms to work on increasingly large and complex data sets.
- Review and evaluate OBI 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 OBI documentation for completeness, accuracy, and thoroughness, and provide detailed feedback to owners and developers.
- Provide consultation and guidance to data and AA owners, developers, and stakeholders on OBI governance and knowledge modeling, including best practices for system development, testing, and deployment.
- Assist analytic methodologists and AA owners in translating technical documentation into analytic tradecraft compliant language.
- Collaborate with team members to identify and implement practices for responsible AI development, including but not limited to bias detection, hallucination recognition, prompt fairness testing, adherence to analytic tradecraft standards and security policies.
- 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.
- Collaborate with the team members to develop and implement testing methodologies for system validation and evaluation leveraging qualitative and quantitative metrics (e.g. consistency, method or reasoning completeness, coverage of method or model for proposed solution).
- Conduct audits to ensure compliant use of systems for approved use-cases in all source analysis.
- Develop and maintain a repository of audit findings and recommendations to facilitate knowledge sharing and best practices across the organization.
- Design and execute TEVV protocols to evaluate the performance, robustness, and fairness of systems in all source analysis contexts.
- Develop and apply statistical models and methods to analyze TEVV results and identify areas for improvement.
- Collaborate with stakeholders to develop and implement corrective actions to address TEV findings.
- Develop and track performance metrics to evaluate the effectiveness of systems in all source analysis.
- Analyze and interpret performance metrics to identify trends, patterns, and areas for improvement.
- Collaborate with stakeholders to develop and implement data-driven decision-making processes to inform system development and improvement.
- Develop and refine methodologies for evaluating system performance, robustness, and fairness in all source analysis contexts.
- Collaborate with stakeholders to develop and implement best practices for system development, testing, and deployment.
- Supports capability development by contributing, editing, and storing code in Government owned/controlled source version control repositories.
Required qualifications/skills:
Minimum 3 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.
-OR-
- A minimum of 7 years of experience related to the specific labor category with at least a portion of the experience within the last 2 years may be substituted for a bachelor’s degree.
Come on board with a company that Values its Employees!
Celestar Corporation is an Equal Opportunity Employer. The Celestar Corporation prohibits discrimination, harassment, and retaliation in employment based on race; color; religion; genetic information; national origin; sex (including same-sex); sexual orientation; gender identity; pregnancy, childbirth, or related medical conditions; age; disability or handicap; citizenship status; marital status; service member/protected veteran status; or any other category protected by federal, state, or local law.
