Arcfield's Cyber programs are expanding and currently in need of Data Scientist, Level 2 (Intermediate) professionals to provide data management and analysis to assist in recommending changes to the Government that can improve operational effectiveness and support decision making.
Requirements
- Demonstrate ability to prepare and analyze data visualizations
- Demonstrate ability to select appropriate analytical approaches towards automation
- Demonstrate ability to review and refine requirements for data science cybersecurity approaches
- Demonstrate strong understanding of Large Language Models (LLMs)
- Demonstrate strong understanding of machine learning principles, techniques, and technologies
- Demonstrate strong knowledge of data engineering
- Demonstrate strong knowledge of data management
Responsibilities
- Extract, transform, load, analyze and interpret relevant information assurance (IA) data for timely analytic use
- Provide reports on any associated patterns, anomalies, and potential security concerns
- Analysis of historical data to gain insights and understand patterns, anomalies, and potential security considerations, and present findings in a clear and concise manner
- Conducting predictive analytics to prepare predictive models and algorithms to identify, characterize, and forecast future outcomes and use prescriptive analytics to recommend optimal actions
- Integrating analytic findings and outcomes into other cybersecurity products and processes, including Continuous Monitoring, to enhance operational effectiveness, support decision-making, and strengthen the strategic intelligence posture
- Conducting ongoing research on emerging data science methodologies and technologies to provide reports and recommendations for adopting emerging data science methodologies
- Assisting in creating, editing, managing, and archiving information within data sources
Other
- Must possess and be able to maintain a TS/SCI clearance with Poly
- 5 years’ relevant experience in data science, mathematics, statistics, business analytics or equivalent quantitative field
- Familiar with Agile processes (Scrum, Jira, Confluence)
- Strong understanding of common tools and technologies (AWS, Spark, Kafka, Tableau, Python, R, Splunk, etc.)
- Exposure to cybersecurity applications or operations
