Data Scientist (Data Architect/Data Engineer/AI-ML Specialist)

Defense Counterintelligence and Security Agency; United States; On-site; USD 90,000 - 130,000; Full time

Job summary

Defense Counterintelligence and Security Agency (NBIS) is seeking a non-supervisory Data Scientist (Data Architect/Data Engineer/AI-ML Specialist) to provide expertise in diverse data science applications and methods. The role emphasizes statistical, ML, and NLP techniques for structured and unstructured data, with responsibility for data-driven decision support.

The incumbent will engage in problem definition, data acquisition, preparation, and modeling, using SQL, Python, and reporting tools

Qualifications

• Degree in a STEM field (1560 series) or equivalent combination of education and experience.
• Transcript submission is required for eligibility.
• Specialized experience demonstrating data science competencies and data-driven decision support.

Responsibilities

• Assist in applying statistical, ML, NLP methods to structured and unstructured data.
• Support design, development, and validation of predictive models and data-driven analyses.
• Independently execute components of data analysis projects from problem definition to modeling using SQL, Python, and visualization tools.
• Lead components of data analysis projects and demonstrate data mining and data management competencies.

Skills

Statistical methods

Machine learning

Natural language processing

Predictive modeling

SQL

Python

Data visualization

Data management

Education

Bachelor's degree in Mathematics/Statistics/Computer Science/Data Science or related field

Tools

Cloudera Data Platform

Cloudera Data Flow (Apache NiFi)

Tableau

DataWalk

JIRA

Agile

Job description

DCSA Acquisition and Technology, National Background Investigation Services (NBIS) is seeking a non-supervisory Data Scientist (Data Architect/Data Engineer/AI-ML Specialist)

The incumbent will provide support, guidance and expertise in various Data Scientist functions. Performs a variety of duties that involve knowledge of a wide variety of Data Scientist applications, environments, and methods.

This position has a Basic Requirement for the 1560: Degree: Mathematics, statistics, computer science, data science or field directly related to the position.

The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.

or Combination of education and experience: Courses equivalent to a major field of study (30 semester hours) as shown in paragraph A above, plus additional education or appropriate experience.

*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: Data Science Series 1560 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 11/13/2026 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.

For the GG-11 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-09 in the Federal service and are prepared to take on greater responsibility. Generally, this would include one year or more of such specialized experience.

• Assisting in applying statistical, machine learning, natural language processing, or other advanced analytical methods to solve problems involving structured and unstructured data.
• Supporting the design, development, and validation of predictive models, quantitative analyses, and data-driven decision-support products under guidance.
• Independently executing components of data analysis projects from problem definition through data acquisition, preparation, and modeling (using SQL, Python, Power BI, or other tools).

For the GG-12 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-11 in the Federal service and are prepared to take on greater responsibility. Generally, this would include one year or more of such specialized experience.

• Applying statistical, machine learning, natural language processing, or other advanced analytical methods to solve complex problems involving structured and unstructured data.
• Designing, developing, and refining predictive models, quantitative analyses, and data-driven decision-support products.
• Leading components of data analysis projects from problem definition through data acquisition, preparation, and modeling.
• Specifically you will be evaluated on the following competencies: Data Mining - Computing process of discovering patterns in a large data set involving methods at the intersection of machine learning, statistics, and database systems.
• Data Management - Knowledge of the principles, procedures, and tools of data management, such as modeling techniques, data backup, data recovery, data dictionaries, data warehousing, data mining, data disposal, and data standardization processes.
• Software and Programming - Leverage and optimize the use of existing OIG specific software (such as Cloudera Data Platform, Cloudera Data Flow (Apache Nifi), Tableau, DataWalk), while recommending future software mix. Understand a variety of programming languages (such as Java/Javascript, Scala, Python, C/C#/C++, R) as needed to meet software and business needs.
• Understand a variety of data warehousing platforms (such as Cloudera/Hive, Oracle, SQL, MySQL, NoSQL), big data software (such as Tableau, DataWalk, Apache Hadoop/Spark, ArcGIS), and data science project management and version control applications (such as JIRA, Agile).
• Qualitative / Quantitative Analysis - Developing and applying quantitative and qualitative analytic methods to identify, collect, process, and analyze large data sets.