Responsibilities

A data scientist will develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets; prototype or consider several algorithms and decide upon final model based on suitable performance metrics; build models or develop experiments to generate data when training or example datasets are unavailable; generate reports and visualizations that summarize datasets and provide data-driven insights to customers; partner with subject matter experts to translate manual data analysis into automated analytics; implement prototype algorithms within production frameworks for integration into analyst workflows.

 

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Keywords: Data analysis software such as R, Python, SAS, or MATLAB, data formats (e.g., SQL tables, structured metadata, network logs), standard techniques and metrics (e.g. cross validation, ROC curves, confusion matrices);  Artificial Intelligence (AI), Large Language Model (LLM), Machine Learning (ML), AI/ML algorithms, statistical analysis, RAG, agents, and agentic workflow 

Qualifications

BASIC QUALIFICATIONS:

• Bachelor's degree from an accredited college or university in a quantitative discipline (e.g., statistics, mathematics, operations research, engineering or computer science) and five (5) years of experience analyzing datasets and developing analytics as well as five (5) years of experience programming with data analysis software such as R, Python, SAS, or MATLAB.
• An additional four (4) years of experience in software development, cloud development, analyzing datasets, or developing descriptive, predictive, and prescriptive analytics can be substituted for a Bachelor's degree.
• A PhD from an accredited college or university in a quantitative discipline can be substituted for four (4) years of experience. 
• Produce data visualizations that provide insight into dataset structure and meaning  
• Work with subject matters experts (SMEs) to identify important information in raw data and develop scripts that extract this information from a variety of data formats (e.g., SQL tables, structured metadata, network logs) 
• Incorporate SME input into feature vectors suitable for analytic development and testing 
• Develop Al and machine learning models to address complex problems. 
• Develop and optimize Large Language Models (LLM) for various NLP tasks and information retrieval 
• Experience with utilizing GPU-based computing resources to accelerate model training and deployment. 
• 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 the performance of analytics using standard techniques and metrics (e.g. cross validation, ROC curves, confusion matrices) 
• Oversee the development of individual analytic efforts and guide team in analytic development process  

An Active TS/SCI clearance with polygraph is required 

 

Additional Desired Qualifications:  

• AI/ML Integration: Familiarity with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) frameworks, agents, and agentic workflow. 

Benefits: Peraton offers enhanced benefits to employees supporting this critical National Security program, which include heavily subsidized employee benefits coverage for you and your dependents, 25 days of PTO accrued annually up to a generous PTO cap, and eligibility to participate in an attractive bonus plan.

Target Salary Range$176,000 - $282,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual’s experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.