Data Scientist - Cleared (Multiple Levels) - Chantilly, VA
VetJobs Chantilly, Virginia, United States · $82K–$189K/yr
Armed Forces · 51-200 employees
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About the role
The Data Scientist will develop innovative machine learning, statistical analysis, and data mining solutions to support mission-critical national security initiatives. They will contribute to the full model lifecycle, including development, deployment, monitoring, and maintenance of AI/ML infrastructure.
What they look for
Requirements
Candidates must possess an active Top Secret/SCI clearance with a Polygraph and be U.S. citizens. Experience requirements vary by level, ranging from a high school diploma with 6 years of experience to a bachelor's degree with 5 years of experience.
Full description
Job Description
ATTENTION MILITARY AFFILIATED JOB SEEKERS - Our organization works with partner companies to source qualified talent for their open roles. The following position is available to Veterans, Transitioning Military, National Guard and Reserve Members, Military Spouses, Wounded Warriors, and their Caregivers. If you have the required skill set, education requirements, and experience, please click the submit button and follow the next steps. Unless specifically stated otherwise, this role is "On-Site"
Data Scientist - Cleared (Multiple Levels)
Noblis is seeking Data Scientists at all experience levels with an active TS/SCI with a Polygraph to support mission-critical national security initiatives in Chantilly, Virginia.
As a Data Scientist, you will support the intelligence community by developing innovative, data-driven solutions to address mission-critical challenges. You will provide technical expertise to government customers through the development of machine learning, statistical analysis, and data mining solutions. You will collaborate with cross-functional teams including data scientists, software engineers, subject matter experts, and cyber analysts to apply advanced analytics, machine learning, and AI techniques. Additionally, you will contribute to the full model lifecycle, including model development, versioning, deployment, monitoring, and vulnerability identification.
Your work will directly contribute to capabilities such as object detection, data triage, search optimization, inference, facial recognition, behavior analysis, and automated decision-making.
The ideal candidate will have experience analyzing cyber data and applying data science methodologies to solve complex customer problems, with strong proficiency in Python and experience working with modern AI/ML technologies and cloud-based environments.
Key Responsibilities • Analyze large volumes of structured and unstructured data using open-source datasets, statistical software, cloud services, and AI/ML technologies to identify meaningful patterns, relationships, and insights
- Support production AI/ML infrastructure and operations, including platform maintenance, issue triage, troubleshooting, and user support
- Support Kubernetes-based platform operations, including the use of management and deployment tools to maintain and optimize AI/ML environments
- Work with containerized model-serving environments, contributing to configuration updates, authentication, troubleshooting, and operational support for LLM and multimodal AI capabilities
- Explore and model data to identify relevant patterns, trends, relationships, and features of interest
- Design, develop, train, evaluate, and refine machine learning models to support mission-focused applications
- Collect, curate, clean, transform, and process large-scale structured and unstructured datasets for analytical and machine learning applications
- Research, implement, evaluate, and document analytical methodologies, models, and outcomes
- Leverage high-performance computing (HPC) resources, including GPU clusters and cloud-based platforms, to support large-scale data processing and model development
- Develop data visualizations and analytical products using tools such as Tableau to effectively communicate findings and recommendations to technical and non-technical stakeholders
Required Experience
Required Qualifications• Active Top Secret/SCI (TS/SCI) with Polygraph
- U.S. Citizenship is required
One of the following:
Level I • Bachelor's or Master's degree with 1 year of related experience including exposure or coursework in data science tools and technologies such as Python; OR Associate's degree with 3 years of related experience; OR High School diploma/GED with 6 years of related experience
- Compensation: $82,500 - $128,925
Level II • Bachelor's degree with 3 years of related experience; OR Master's degree with 1 year of related experience; OR Associate's degree with 6 years of related experience; OR High School diploma/GED with 9 years of related experience
- Experience with data science tools and technologies, including analyzing data in Python
- Compensation: $90,700 - $141,775
Level III • Bachelor's degree with 5 years of related experience; OR Master's degree with 3 years of related experience; OR Associate's degree with 8 years of related experience; OR High School diploma/GED with 11 years of related experience
- Experience with data science tools and technologies, including analyzing data in Python
- Compensation: $120,700 - $188,725
- Travel up to 10% within US.
- Lift up to 30 lbs, walk, bend, drive.
Preferred Experience
Desired Qualifications• Proficiency in data science tools and technologies such as SQL/PostgreSQL, Apache Spark, and Git
- Experience with machine learning, statistical modeling, and/or time-series forecasting
- Experience with data visualization tools such as Tableau to communicate findings to technical and non-technical stakeholders
- Experience working with cloud platforms such as AWS
- Experience working with cyber data, including platforms such as Shodan and Censys
- Experience working with open-source and large-scale datasets
- Demonstrated ability to clean, transform, manage, and optimize large, complex datasets for analytical and machine learning applications
- Fundamental understanding of a range of AI/ML techniques, with the ability to select and apply appropriate methods to address specific problems
- Strong written and verbal communication skills, with the ability to effectively communicate technical concepts and analytical findings to diverse audiences
- Familiarity with developing, retraining, or using AI and machine learning packages
- Knowledge of software and hardware optimization techniques for large-scale data processing
- Proficiency in data warehousing, data management, and ETL tools (e.g., Apache NiFi, Pentaho, Kafka)
- Experience supporting Kubernetes-based platform operations and containerized model-serving environments
- Advanced degree in a data science equivalent field or sub-field
Certificates/Security Clearances/Other
- Active TS/SCI w/ polygraph
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