Data Scientist - Cleared (Multiple Levels)

Noblis delivers advanced scientific, engineering, and management solutions to support critical federal missions, including defense and intelligence initiatives. The company is seeking Data Scientists at multiple experience levels to develop and operate data-driven, machine learning, and AI solutions for national security customers, including model development, deployment, monitoring, and advanced analytics.

What you'll do:

• 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

What they're looking for:

• • Active Top Secret/SCI (TS/SCI) with Polygraph
• • U.S. Citizenship is required
• • 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
• • 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
• • 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
• • Travel up to 10% within US
• • Lift up to 30 lbs, walk, bend, drive
• • 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

Benefits:

• Health benefits for eligible full-time and part-time employees working at least 20 hours a week on a regular basis
• Life benefits for eligible full-time and part-time employees working at least 20 hours a week on a regular basis
• Disability benefits for eligible full-time and part-time employees working at least 20 hours a week on a regular basis
• Financial benefits for eligible full-time and part-time employees working at least 20 hours a week on a regular basis
• Retirement benefits for eligible full-time and part-time employees working at least 20 hours a week on a regular basis
• Paid leave for eligible full-time and part-time employees working at least 20 hours a week on a regular basis
• Professional development for eligible full-time and part-time employees working at least 20 hours a week on a regular basis
• Tuition assistance for eligible full-time and part-time employees working at least 20 hours a week on a regular basis
• Work-life programs for eligible full-time and part-time employees working at least 20 hours a week on a regular basis
• Award programs acknowledging employees for exceptional performance and superior demonstration of service standards