Cyber Data Scientist

Remote (United States)

About the Role

This opportunity is for a Cyber Data Scientist responsible for developing, deploying, and improving analytical models that support automation, insights, and better decision-making. The role works closely with digital product teams, cybersecurity teams, IT engineering teams, and internal stakeholders to shape analytical solutions and support production workflows.

The position involves applying statistics, artificial intelligence, machine learning, programming, data transformation, and cloud-based model orchestration to large datasets and cybersecurity-related workflows.

Status

Full-Time

Pay

Base Salary Range: $130,000 – $140,000 per year

What You’ll Do

• Develop and deploy analytical models on data and processes to generate insights, support automation, and improve decision-making.
• Collaborate with digital product teams and internal stakeholders to shape, enable, and migrate production workflows.
• Apply statistics, artificial intelligence, and machine learning techniques to large datasets.
• Use multiple programming languages and data transformation tools to support model development and analysis.
• Work with databases, data structures, and data architectures to support scalable analytical solutions.
• Create visualizations, presentations, and clear quantitative summaries for technical and non-technical audiences.
• Explore and adopt new technologies provided by IT engineering and cybersecurity teams.
• Work independently with limited supervision while maintaining strong attention to detail and effective collaboration.
• Mentor junior cyber data scientists.

Qualifications

• Bachelor’s degree and 6 years of experience in the data science field.
• Four additional years of related experience may substitute for the degree requirement.
• Proficiency in mathematical modeling, including modeling theory, modeling and identification strategies, and understanding limitations or pitfalls.
• Experience with relational database management systems and open-source frameworks.
• Experience with machine learning or artificial intelligence.
• Familiarity with the Risk Management Framework (RMF) process.
• Ability to work in a federal delivery environment.