Data Scientist - Cleared (Multiple Levels)

Noblis•Reston, VA

1d•Hybrid

About The Position

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.

Requirements

Active Top Secret/SCI (TS/SCI) with Polygraph
U.S. Citizenship is required
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
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
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

Nice To Haves

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

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