Revolutional delivers advanced technology solutions and mission support to federal agencies across civilian, health, and national security environments. We apply modern capabilities, including AI/ML, cloud, cybersecurity, and IT modernization to solve complex challenges, enable faster and more secure operations, and drive measurable mission outcomes.

We are redefining how federal technology gets built and delivered by operating with a product mindset, prioritizing speed, ownership, and execution over bureaucracy.

Lead Data Scientist

Location: Suitland, MD (Hybrid)

Terms: Full-time

Clearance/Work Authorization: U.S. Citizenship with the ability to obtain and maintain a Public Trust is required

Salary Range: $150-210k DOE

Travel: %

Project Description

This position supports Revolutional’s federal customer as part of an application transformation and modernization initiative.

This program is driving a large-scale transformation of systems into a data-centric, cloud-native ecosystem capable of supporting high-volume, near real-time data processing and advanced analytics. The work includes modernization of legacy applications, development of new cloud-native solutions, and implementation of DevSecOps and scaled Agile practices across the organization.

The core challenge: orchestrating complex, multi-contractor delivery while transforming both technology and operating models without disrupting mission-critical operations.

Position Description

As a Lead Data Scientist at Revolutional, you will define and drive enterprise data science and AI/ML strategy across a large-scale federal modernization program.

You will lead efforts spanning advanced analytics, machine learning, MLOps, AI governance, and operational analytics integration across complex enterprise systems. This role requires close collaboration with data engineering, architecture, application development, and operational teams to ensure AI/ML capabilities are production-ready, scalable, explainable, and integrated into enterprise workflows.

You will operate at both strategic and hands-on levels guiding technical direction, developing advanced models, and ensuring analytics solutions deliver measurable mission impact.

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 NLP, LLMs, deep learning, reinforcement learning, anomaly detection, and time series analysis
Design and support event-driven analytics and real-time/streaming ML pipelines
Collaborate with data engineers, architects, application teams, and SMEs to integrate AI/ML capabilities into enterprise systems and operational workflows
Support system-of-systems (SoS) 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

Technical Environment

Cloud-native AI/ML and analytics environments (AWS, Azure)
Distributed data platforms and enterprise analytics ecosystems
Python, R, Spark, TensorFlow, PyTorch, Databricks, and related ML frameworks
MLOps pipelines, model deployment platforms, and automation frameworks
Real-time streaming and event-driven analytics systems
DevSecOps pipelines and CI/CD automation practices
DataOps and Agile/SAFe delivery environments
APIs, distributed integrations, and enterprise data platforms
Collaboration and delivery tools (Git, Jira, Confluence)
High-volume, near real-time processing environments

What You Bring (Requirements)

Baseline Requirements

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, advanced analytics, or enterprise modernization initiatives
Proven experience leading AI/ML and analytics efforts across large-scale, complex systems
Ability to obtain and maintain a Public Trust clearance

Technical Capabilities

Deep expertise in machine learning, statistical modeling, and advanced analytics techniques
Experience implementing end-to-end MLOps pipelines including model training, validation, deployment, monitoring, and scaling
Experience with NLP, LLMs, deep learning, reinforcement learning, anomaly detection, and time series analytics
Experience designing and supporting real-time or streaming analytics architectures
Experience integrating AI/ML solutions across system-of-systems (SoS) environments and distributed enterprise platforms
Experience implementing AI governance frameworks addressing explainability, fairness, transparency, and bias mitigation
Experience with large-scale distributed data environments and cloud-native analytics platforms
Experience with DataOps, CI/CD integration, and Agile/SAFe delivery models
Strong experience with Python, R, Spark, TensorFlow, PyTorch, Databricks, and related AI/ML technologies
Experience developing dashboards, technical reports, analysis plans, and reproducible analytics workflows
Experience collaborating across engineering, architecture, application, and operational teams at enterprise scale

Core Strengths

Strong ownership mindset with accountability for enterprise AI/ML outcomes
Ability to translate complex analytical findings into actionable business and mission insights
Strategic thinker capable of balancing innovation, governance, and operational realities
Effective communication across technical, operational, and executive stakeholders
Strong leadership and mentoring capabilities across data science and analytics teams
Ability to operate in complex, fast-moving, multi-contractor delivery environments

Nice to Have (Differentiators)

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

#DICE #Linkedin

___________________________________________________________________________________________________________

Here at Revolutional we are pleased to have been repeatedly recognized for our outstanding work culture, the innovative work we do, and the employees on our team who make a difference each day. Some of these recognitions include:

Recognized as a Top 20 "Best Place to Work in Virginia"
Recipient of Department of Labor's HireVets Gold Medallion
Great Place to Work Certification for five years running
A Virginia Chamber of Commerce Fantastic 50 company
A Northern Virginia Technology Council Tech 100 company
Inc. 5000 list of fastest growing companies for eleven years
Two-time SBA SBIR Tibbett's Award winner
Virginia Values Veterans (V3) Certification

We recognize that every bit of our success is the result of our teams of hard-working, motivated, and innovative professionals who are proud to call themselves part of the Revolutional family! In addition to competitive compensation, a family-focused culture, and a dynamic, productive work environment, we offer all full-time employees a variety of benefits including, but not limited to

Traditional and HSA- eligible medical insurance plans
100% employer-paid dental and vision insurance options
100% employer-sponsored STD, LTD, and life insurance
5% 401(k) company matching
Flexible-schedules and teleworking options
Paid holidays and PTO Accrual Plans
Paid Parental Leave
Professional development and career growth opportunities
Team and company-wide events, recognition, and appreciation-- and so much more!

Check out our Revolutional | LinkedIn to find out a little more about who we are and if we are the right next step for your career!

Revolutional is an Equal Opportunity Employer providing equal employment opportunity to all employees and applicants for employment without regard to race, color, religion, national origin, age, gender, gender identity, sexual orientation, disability, or genetics. Revolutional does and will take affirmative action to employ and advance in employment individuals with disabilities and protected veterans. To perform the above job successfully, an individual must possess the knowledge, skills, and abilities listed; meet the education and work experience required; and must be able to perform each essential duty and responsibility satisfactorily. Other duties in addition to those listed may be assigned as necessary to meet business needs. Reasonable accommodation will be made to enable an applicant with a disability to successfully apply for and/or perform the essential duties of the job. If you are in need of an accommodation, please contact HR@revolutional.com.

“Know Your Rights: Workplace Discrimination is Illegal” Poster | U.S. Equal Employment Opportunity Commission

Revolutional, LLC

Latest Jobs

Lead Data Scientist