Mid-level Data Scientist; OBI Advanced Analytic Method Augmentation - OBIQUA

Celestar Corporation is seeking a Mid-level Data Scientist (OBI Advanced Analytic Method Augmentation) 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:
December 2025/ January 2026

Anticipated start:
February/March 2026

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

Celestar is a proud Veteran‑Owned company, offering 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.

• 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.
• Skilled in data visualization and use of graphical applications including Microsoft Power BI and Tableau; major data science languages such as R, Python; managing and merging disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms.
• Has prior experience with large data multi‑INT analytics, ML, and automated predictive analytics.
• Designs, develops, and evaluates leading‑edge algorithmic intelligence concepts, practices, and technologies for implementation into 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.
• Evaluates data science, artificial intelligence, and other advanced analytic methods for risks, biases, and limitations that would distort conclusions.
• Conducts continuous independent research on methods of analysis in government, industry, and academia to keep abreast of the state of the art, keeping 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.
• Provides technical input into and participates in the development of software and computer graphics systems.
• 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 R or Python scripts to drive data science workflows, has experience using SQL, and managing and merging disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms.
• Possesses prior experience with large data, spatial data,…