Data Scientist

US Defense Counterintelligence and Security Agency; Hanover (MD); On-site; USD 90,000 - 120,000; Full time

Job summary

DCSA Acquisition and Technology, NBIS is seeking a Data Scientist capable of applying statistical methods, performing data analysis, and contributing to algorithm development. The role emphasizes data mining, data management, and cross-functional software skills to support analytical objectives.

Qualified candidates will have a degree in a relevant field and experience with programming languages such as Python/SQL, plus familiarity with data warehousing and big data tools.

Qualifications

• Degree in mathematics, statistics, computer science, data science or related field at baccalaureate level.
• Combination of education and experience—courses equivalent to a major field plus additional experience.
• Transcript submission is required to avoid ineligibility.
• Qualifying experience as described must show competencies for the GS/GG-05 level, typically one year or more.

Responsibilities

• Apply foundational statistical methods and basic mathematical concepts.
• Assist with statistical programming using R/Python/SQL.
• Lead development of algorithms leveraging R, Python, or SQL/NoSQL.
• Evaluate data using data mining, management, and analytic methods.

Skills

Data Mining

Data Management

Software & Programming

Qualitative / Quantitative Analysis

Education

Bachelor's degree in Mathematics/Statistics/CS/Data Science

Tools

Cloudera Data Platform

Cloudera Data Flow / Apache Nifi

Tableau

DataWalk

Python

SQL/NoSQL

Hadoop/Spark

JIRA / Agile

Job description

DCSA Acquisition and Technology, National Background Investigation Services (NBIS) is looking for 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. Visit www.dcsa.mil 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.

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 10/12/2026

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-05 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:

GG-07

Applying foundational statistical methods (e.g. regression, decision trees, or probability) using basic mathematics, including logarithms, trigonometry, linear algebra, calculus, statistics and operational analysis. Conducting basic risk assessments. Assisting with statistical and general-purpose programming languages for data analysis. Writing basic algorithms leveraging R, Python, or SQL/NoSQL to support the development or testing of analytical models, and explaining the results to teammates.

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-07 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:

GG-09

Applying statistical methods (e.g. regression, decision trees, or probability) using basic mathematics, including logarithms, trigonometry, linear algebra, calculus, statistics and operational analysis. Conducting standard risk assessments. Applying statistical and general-purpose programming languages for data analysis. Leading the development of algorithms leveraging R, Python, or SQL/NoSQL.

Specifically you will be evaluated on the following competencies

1. Data Mining - Computing process of discovering patterns in a large data set involving methods at the intersection of machine learning, statistics, and database systems.
2. 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.
3. 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).
4. Qualitative / Quantitative Analysis - Developing and applying quantitative and qualitative analytic methods to identify, collect, process, and analyze large data sets.