Lead Data Scientist — AI/ML for Federal Modernization

Harmonia Holdings Group, LLC; McLean (VA); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Hybrid work options

Professional development

Competitive benefits

Job summary

Revolutional is seeking a Lead Data Scientist to define and drive enterprise AI/ML strategy across a large federal modernization program. You will lead advanced analytics, MLOps, AI governance, and operational analytics integration across complex enterprise systems.

This role requires collaboration with data engineering, architecture, application development, and operations teams to ensure scalable, explainable AI/ML capabilities.

Qualifications

• U.S. Citizenship with the ability to obtain a Public Trust
• PhD in Data Science, Computer Science, Statistics, Mathematics, or related field
• 15+ years of experience in data science, AI/ML, or enterprise modernization
• Proven experience leading AI/ML across large-scale, complex systems
• Ability to obtain and maintain a Public Trust clearance

Responsibilities

• Provide technical leadership across enterprise data science and AI/ML initiatives
• Design, develop, validate, deploy, monitor, and scale ML and analytics solutions in production
• Lead implementation of MLOps for model lifecycle management, automation and observability
• Apply NLP, LLMs, deep learning, RL, anomaly detection, and time-series analytics
• Collaborate with data engineers, architects, application teams, and SMEs
• Support system-of-systems integrations across multiple vendors and platforms
• Develop reproducible analytics workflows, documentation, dashboards, and reports
• Mentor data scientists and promote best practices

Skills

PhD in Data Science

Public Trust clearance

15+ years experience

Education

PhD in Data Science

Tools

Python

R

Spark

TensorFlow

PyTorch

Databricks

Job description

Revolutional is seeking a Lead Data Scientist to define and drive enterprise AI/ML strategy across a large federal modernization program. You will lead advanced analytics, MLOps, AI governance, and operational analytics integration across complex enterprise systems.

This role requires collaboration with data engineering, architecture, application development, and operations teams to ensure scalable, explainable AI/ML capabilities.