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Revolutional

Modernizes agency systems and defends infrastructure

Lead Data Scientist

Applied Machine LearningConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • U.S. citizenship and the ability to obtain and maintain a Public Trust are required.
  • A PhD in Data Science, Computer Science, Statistics, Mathematics, or a related field is required.
  • At least 15 years of experience in data science, artificial intelligence/machine learning, advanced analytics, or enterprise modernization initiatives are required.
  • Proven experience leading artificial intelligence/machine learning and analytics efforts across large-scale, complex systems is required.
  • Deep expertise in machine learning, statistical modeling, and advanced analytics techniques is required.
  • Experience implementing end-to-end MLOps pipelines, including model training, validation, deployment, monitoring, and scaling, is required.
  • Experience with natural language processing, large language models, deep learning, reinforcement learning, anomaly detection, and time series analytics is required.
  • Experience designing and supporting real-time or streaming analytics architectures is required.
  • Experience integrating AI/ML solutions across system-of-systems environments and distributed enterprise platforms is required.
  • Experience implementing AI governance frameworks addressing explainability, fairness, transparency, and bias mitigation is required.
  • Experience with large-scale distributed data environments and cloud-native analytics platforms is required.
  • Experience with DataOps, continuous integration/continuous delivery integration, and Agile/SAFe delivery models is required.
  • Strong experience with Python, R, Spark, TensorFlow, PyTorch, Databricks, and related AI/ML technologies is required.
  • Experience developing dashboards, technical reports, analysis plans, and reproducible analytics workflows is required.
  • Experience collaborating across engineering, architecture, application, and operational teams at enterprise scale is required.
  • The candidate must be able to translate complex analytical findings into actionable business and mission insights and communicate effectively with technical, operational, and executive stakeholders.
  • The candidate must demonstrate leadership and mentoring capabilities across data science and analytics teams and be able to operate in complex, fast-moving, multi-contractor delivery environments.

Responsibilities

  • Provide technical leadership across enterprise data science and AI/ML initiatives within a large-scale modernization program.
  • Design, develop, validate, deploy, monitor, and scale machine learning and advanced analytics solutions in production environments.
  • Lead implementation of MLOps practices supporting model lifecycle management, automation, observability, and continuous improvement.
  • Apply advanced data science techniques, including natural language processing, large language models, deep learning, reinforcement learning, anomaly detection, and time series analysis.
  • Design and support event-driven analytics and real-time/streaming machine learning pipelines.
  • Collaborate with data engineers, architects, application teams, and subject-matter experts to integrate AI/ML capabilities into enterprise systems and operational workflows.
  • Support system-of-systems integrations across multiple systems, vendors, contractors, and interdependent platforms.
  • Establish AI governance frameworks supporting fairness, bias mitigation, explainability, transparency, and compliance with standards such as the NIST AI Risk Management Framework.
  • Develop reproducible analytics workflows, technical documentation, analysis plans, dashboards, and reporting deliverables.
  • Support DataOps and Agile data science practices, including iterative development, pipeline automation, CI/CD integration, and collaborative model delivery.
  • Ensure analytics solutions align with enterprise security, privacy, and compliance requirements.
  • Drive improvements in data quality, validation, accessibility, and operational analytics reliability.
  • Present findings, recommendations, and technical approaches to executive leadership and stakeholders.
  • Mentor data scientists and analytics teams while promoting best practices across the organization.

Desired Qualifications

  • Experience supporting statistical and similarly large-scale federal modernization programs.
  • Experience implementing enterprise AI governance or responsible AI initiatives.
  • Experience with event-driven architectures, streaming analytics, or operational AI systems.
  • Experience supporting large-scale data modernization or enterprise analytics transformation efforts.
  • Experience working within DevSecOps-enabled AI/ML delivery environments.

About the Company

Revolutional

Modernizes agency systems and defends infrastructure

Revolutional helps government agencies modernize IT systems, strengthen cybersecurity, and deliver results without slowing missions. It combines IT modernization, secure infrastructure, and rapid project delivery tailored to agency needs. It differentiates itself by prioritizing fast, safe outcomes that fit within mission constraints and government requirements. Its goal is to enable agencies to complete their missions efficiently by updating technology and defense capabilities.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
McLean, VA
Founded
Not listed

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