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Peraton

Runs and secures technology for federal agencies

Data Scientist Engineer Level 2

Applied Machine Learning +1Confirmed live in the last 24 hours
Full-timeLaurel, MD, USAIn-person

About the Job

Requirements

  • A bachelor's degree from an accredited college or university in a quantitative discipline, such as statistics, mathematics, operations research, engineering, or computer science, and five years of experience analyzing datasets and developing analytics, as well as five years of experience programming with data analysis software such as R, Python, SAS, or MATLAB.
  • An additional four years of experience in software development, cloud development, analyzing datasets, or developing descriptive, predictive, and prescriptive analytics may be substituted for a bachelor's degree.
  • A PhD from an accredited college or university in a quantitative discipline may be substituted for four years of experience.
  • Experience utilizing GPU-based computing resources to accelerate model training and deployment.
  • An active TS/SCI clearance with polygraph is required.

Responsibilities

  • Produce data visualizations that provide insight into dataset structure and meaning.
  • Work with subject matter experts to identify important information in raw data and develop scripts that extract this information from a variety of data formats, such as SQL tables, structured metadata, and network logs.
  • Incorporate subject matter expert input into feature vectors suitable for analytic development and testing.
  • Develop AI and machine learning models to address complex problems.
  • Develop and optimize large language models for various natural language processing tasks and information retrieval.
  • Develop and implement statistical, machine learning, and heuristic techniques to create descriptive, predictive, and prescriptive analytics.
  • Develop statistical tests to make data-driven recommendations and decisions.
  • Develop experiments to collect data or models to simulate data when required data are unavailable.
  • Develop feature vectors for input into machine learning algorithms.
  • Identify the most appropriate algorithm for a given dataset and tune input and model parameters.
  • Evaluate and validate analytics performance using standard techniques and metrics, such as cross-validation, ROC curves, and confusion matrices.
  • Oversee the development of individual analytic efforts and guide the team in the analytic development process.

Desired Qualifications

  • Familiarity with large language models and Retrieval-Augmented Generation frameworks, agents, and agentic workflows.

About the Company

Peraton

Runs and secures technology for federal agencies

Peraton builds and runs secure technology for American defense, intelligence, space, and civilian agencies, from military networks to satellite ground stations. In 2025, the Federal Aviation Administration chose it to manage the overhaul of the nation's air traffic control system, replacing copper wiring with fiber and upgrading radar and radios. Its engineers, many holding security clearances, run and defend agency networks and data centers, write mission software, and operate space and communications systems, and agencies pay for this work through multiyear contracts. Peraton was formed in 2017, when private-equity firm Veritas Capital bought Harris Corporation's government IT business, and is based in Reston, Virginia.

Company size
10,001+
Company stage
Grant
Total funding
$60M
Headquarters
Reston, VA
Founded
2017

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