COMPUTER SCIENTIST

DCSA Acquisition and Technology, National Background Investigation Services (NBIS) is seeking a Computer Scientist/Data Engineer (GG-13). The incumbent will serve as a technical advisor, developing advanced AI/ML, NLP, and cloud data architectures to safeguard the federal workforce. This role requires strong programming skills (Python/SQL) and containerization expertise. Visit to learn more about DCSA.

This position has a Basic Requirement for the 1550: Bachelor's degree in computer science or bachelor's degree with 30 semester hours in a combination of mathematics, statistics, and computer science. At least 15 of the 30 semester hours must have included any combination of statistics and mathematics that included differential and integral calculus. All academic degrees and course work must be from accredited or pre-accredited institutions.

*NOTE: Failure to provide transcripts will result in you being rated ineligible for this position.

The experience described in your resume will be evaluated and screened from the Office of Personnel Management's (OPMs) basic qualifications requirements. See: Computer Science Series 1550 for OPM qualification standards, competencies and specialized experience needed to perform the duties of the position as described in the MAJOR DUTIES and QUALIFICATIONS sections of this announcement by 10/19/2026

Applicant must have directly applicable experience that demonstrates the possession of the knowledge, skills, abilities and competencies necessary for immediate success in the position. Qualifying experience may have been acquired in any public or private sector job, but will clearly demonstrate past experience in the application of the particular competencies/knowledge, skills and abilities necessary to successfully perform the duties of the position.

You must have specialized experience sufficient to demonstrate that you have acquired all the competencies necessary to perform at a level equivalent in difficulty, responsibility, and complexity to the next lower grade (GS/GG-12) in the Federal service and are prepared to take on greater responsibility.

Generally, this would include one year or more of such specialized experience.

Specialized experience for this position includes:

1. Applying statistical and general-purpose programming languages (e.g., Python, R, SQL, and C++) to write clean code and build structured data pipelines for advanced data analysis.
2. Implementing programming languages (e.g, C++, SQL, Python, R and other computational languages) to develop complex queries for the support of reporting and advanced analytical and machine learning capabilities.
3. Utilizing natural language processing, text mining, machine learning techniques, and predictive modeling (including decision trees and regression) to transform large volumes of unstructured data into actionable, structured intelligence that supports risk mitigation.
4. Integrating artificial intelligence and data architecture models seamlessly with secure cloud and enterprise IT infrastructure.
5. Utilizing a strong mathematical foundation, specifically linear algebra, calculus, and statistics, to apply rigorous scientific and quantitative methods to evaluate data reliability, perform detailed risk assessments, and design automated data labeling workflows.

Specifically you will be evaluated on the following competencies

1. Artificial Intelligence : This competency requires knowledge of the principles, methods, and tools used to design systems that perform human intelligence functions.
2. Data Analysis : This competency involves the ability to analyze, model, and transform data to highlight useful information, suggest recommendations and conclusions, and support senior leader decision-making.
3. Programming : This competency is the skill to implement design solutions and apply programming languages across multiple platforms and development frameworks.
4. Systems Design : This competency entails the ability to design and evaluate software and hardware and develop enterprise and solution architectures that meet user needs and optimize performance, using applicable principles, methods, and tools.
5. Risk Management : This competency requires knowledge of the principles, methods, and tools used for risk assessment and mitigation, including assessment of failures and their consequences.