Job description

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 may be substituted for a bachelor's degree. A Ph.D. from an accredited college or university in a quantitative discipline may be substituted for four (4) years of experience. • Experience with 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/AL 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. Investing in Your Growth: Selected candidates may be eligible for enhanced professional development opportunities, including training, certification programs, and skill-building experiences tailored to individual strengths, career goals, and role-specific requirements. As a Data Scientist, you will apply advanced data science, machine learning, statistical, and analytical techniques to solve complex, mission-critical challenges supporting national security. You will work closely with technical teams, analysts, subject matter experts, and customer leadership to transform complex data into actionable insights and transition innovative algorithms and research concepts into scalable, production-ready capabilities. This role combines hands-on technical development, applied research, experimentation, and customer engagement, providing the opportunity to influence the direction of emerging analytics capabilities while delivering measurable mission impact. Key Responsibilities • Develop and operationalize advanced analytics: Design, develop, test, and deploy machine learning, statistical, data mining, and graph-based algorithms to solve complex, mission-critical challenges. • Conduct applied research and experimentation: Evaluate emerging technologies, modeling approaches, and analytical methodologies; design experiments and select solutions based on performance, scalability, data availability, and mission requirements. • Transform data into actionable insights: Analyze complex datasets, develop models and projections, and create visualizations and technical products that communicate meaningful, data-driven insights to customers and stakeholders. • Automate and integrate analytics: Partner with subject matter experts and analysts to translate manual processes into automated analytics and integrate prototype algorithms into production systems and operational workflows. • Drive technical collaboration and customer engagement: Serve as a technical representative in customer meetings and reviews, collaborate across engineering and research teams, and communicate technical findings and recommendations to diverse audiences. • Advance mission capabilities: Maintain awareness of emerging AI/ML and data science technologies, identify opportunities for innovation, and contribute to the development of scalable solutions that deliver measurable mission impact. #MDFSP As a Data Scientist, you will apply advanced data science, machine learning, statistical, and analytical techniques to solve complex, mission-critical challenges supporting national security. You will work closely with technical teams, analysts, subject matter experts, and customer leadership to transform complex data into actionable insights and transition innovative algorithms and research concepts into scalable, production-ready capabilities. This role combines hands-on technical development, applied research, experimentation, and customer engagement, providing the opportunity to influence the direction of emerging analytics capabilities while delivering measurable mission impact. Key Responsibilities • Develop and operationalize advanced analytics: Design, develop, test, and deploy machine learning, statistical, data mining, and graph-based algorithms to solve complex, mission-critical challenges. • Conduct applied research and experimentation: Evaluate emerging technologies, modeling approaches, and analytical methodologies; design experiments and select solutions based on performance, scalability, data availability, and mission requirements. • Transform data into actionable insights: Analyze complex datasets, develop models and projections, and create visualizations and technical products that communicate meaningful, data-driven insights to customers and stakeholders. • Automate and integrate analytics: Partner with subject matter experts and analysts to translate manual processes into automated analytics and integrate prototype algorithms into production systems and operational workflows. • Drive technical collaboration and customer engagement: Serve as a technical representative in customer meetings and reviews, collaborate across engineering and research teams, and communicate technical findings and recommendations to diverse audiences. • Advance mission capabilities: Maintain awareness of emerging AI/ML and data science technologies, identify opportunities for innovation, and contribute to the development of scalable solutions that deliver measurable mission impact. #MDFSP 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 may be substituted for a bachelor's degree. A Ph.D . from an accredited college or university in a quantitative discipline may be substituted for four (4) years of experience. • Experience with 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/AL 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. Investing in Your Growth: Selected candidates may be eligible for enhanced professional development opportunities, including training, certification programs, and skill-building experiences tailored to individual strengths, career goals, and role-specific requirements.

Requirements

Must-haves

Experience with produce data visualizations that provide insight into dataset structure and meaning
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
AI/AL Integration: Familiarity with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) frameworks, agents, and agentic workflow
Develop and operationalize advanced analytics: Design, develop, test, and deploy machine learning, statistical, data mining, and graph-based algorithms to solve complex, mission-critical challenges.
Experience with produce data visualizations that provide insight into dataset structure and meaning
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

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

pythonsqlmachine learningllmaiml

Platform: peraton
Effort: medium

Benefits

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Pto

Professional Development