Senior Data Scientist

Peraton•Washington, DC

1d•$146,000 - $234,000

About The Position

We are seeking an experienced Data Scientist / Subject Matter Expert (SME) to support a classified government contract. The successful candidate will provide technical expertise in analyzing and interpreting complex data to inform enterprise data management decisions, identify opportunities for the application of Data Science, and develop innovative solutions that address customer mission requirements. The Data Scientist will support multiple customer organizations and Chief Artificial Intelligence Officer (CAIO) initiatives by identifying and evaluating opportunities to apply advanced analytics, artificial intelligence, and machine learning to customer data assets. The position will help bridge the gap between mission requirements, data assets, and emerging AI/ML capabilities. The role requires extensive collaboration with government stakeholders, technical teams, external customers, and IC partners. The Data Scientist will contribute to the development and implementation of technical solutions, support integration of AI capabilities with existing customer data environments, and help establish repeatable approaches for leveraging Data Science across the enterprise.

Requirements

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Artificial Intelligence, or a related technical discipline; equivalent experience may be considered.
12+ years of relevant experience in Data Science, advanced analytics, machine learning, artificial intelligence, statistics, or a related discipline; Minimum of 10 years with MS/MA; Minimum of 7 years with Ph.D.
Active TS or Q clearance or higher is required. Ability to obtain Q/SCI.
Demonstrated experience analyzing and interpreting complex datasets to produce actionable insights.
Experience developing and implementing Data Science, statistical, or machine learning models.
Strong programming experience with Python, R, or equivalent analytical programming languages.
Strong SQL and experience working with structured and/or unstructured data.
Experience applying statistical analysis, predictive modeling, machine learning, or other advanced analytical techniques.
Demonstrated experience translating mission, business, or operational requirements into analytical and technical solutions.
Experience working with complex enterprise data environments and disparate data sources.
Experience integrating analytical or AI/ML solutions with data platforms, applications, pipelines, or other technical environments.
Understanding of data management principles, including data quality, metadata, data governance, data lineage, data interoperability, and data sharing.
Demonstrated ability to work across multiple organizations and collaborate with diverse technical and mission stakeholders.
Strong problem-solving, communication, presentation, and technical writing skills.
Ability to work independently as an SME while effectively collaborating within multidisciplinary teams.

Nice To Haves

Previous experience supporting the Intelligence Community, Department of Energy, or other U.S. Government mission environments.
Experience supporting a government CAIO, AI, or enterprise Data Science organization.
Experience identifying and evaluating AI/ML use cases within enterprise or mission environments.
Experience integrating AI/ML solutions with existing government data assets and enterprise data platforms.
Experience with generative AI, large language models, natural language processing, computer vision, knowledge graphs, or other advanced AI capabilities.
Experience with cloud-based Data Science and AI environments, including AWS, Azure, or other government cloud platforms.

Responsibilities

Serve as a Data Science SME providing technical leadership and expertise across customer organizations and mission areas.
Analyze, interpret, and derive insights from complex, heterogeneous, and large-scale datasets to support mission and enterprise decision-making.
Identify opportunities to apply Data Science, advanced analytics, artificial intelligence, and machine learning to customer mission challenges.
Assess customer data assets to determine their suitability for advanced analytics and AI/ML applications.
Support CAIO initiatives by identifying, evaluating, prioritizing, and implementing Data Science and AI use cases.
Translate mission and business requirements into Data Science problems, analytical approaches, technical requirements, and implementation strategies.
Develop statistical models, machine learning models, algorithms, and analytical methodologies to address complex customer requirements.
Design and develop prototypes and proof-of-concept solutions to demonstrate the potential value of Data Science and AI capabilities.
Support the transition of successful prototypes and analytical capabilities into operational or production environments.
Integrate AI and Data Science solutions with existing customer data assets, platforms, pipelines, and analytic environments.
Collaborate with data engineers, data architects, software developers, AI/ML engineers, and other technical personnel to develop end-to-end solutions.
Provide technical support to other customer organizations seeking to identify and implement Data Science opportunities.
Coordinate with external customers, mission partners, IC organizations, and other stakeholders to define requirements and develop interoperable technical solutions.
Participate in technical working groups, design sessions, and collaborative forums focused on Data Science, AI, and enterprise data capabilities.
Evaluate emerging Data Science, AI/ML, and analytical technologies and recommend capabilities that can improve customer mission effectiveness.
Assess data quality, availability, structure, provenance, and other characteristics that may affect analytical and AI solution development.
Identify data management challenges and recommend improvements required to enable effective Data Science and AI applications.
Develop reusable analytical methodologies, models, frameworks, and technical approaches that can be applied across multiple customer organizations.
Support development of standards, best practices, and repeatable processes for Data Science experimentation, evaluation, implementation, and operationalization.
Develop analytical documentation, technical specifications, model documentation, methodologies, and implementation plans.
Validate analytical models and results and communicate assumptions, limitations, risks, and findings to technical and non-technical stakeholders.
Brief government leadership and mission stakeholders on Data Science opportunities, analytical findings, technical approaches, and recommendations.
Serve as a trusted technical advisor on the application of Data Science and AI to customer data and mission requirements.
Ensure all solutions and activities comply with applicable security, classification, data governance, privacy, and customer policies.