Data Scientist, Level 3

At Independent Software, as a Data Scientist Level 3, you will support mission-critical national security operations by applying advanced data science, machine learning, and statistical techniques to large-scale, complex datasets.

This role blends data science with cyber threat analysis, requiring a strong understanding of network data, protocols, and adversary activity.

You will work across the full data lifecycle—curating, processing, modeling, and visualizing data—to identify patterns, detect anomalies, and generate actionable insights.

Leveraging strong programming skills and analytical expertise, you will develop automated workflows, refine analytical models, and support data-driven decision-making in dynamic mission environments.

This role is ideal for an inquisitive, discovery-oriented professional who thrives on analyzing complex data, understanding cyber behaviors, and adapting to new tools and technologies.

• Apply machine learning, statistical analysis, and computational techniques to analyze large and complex datasets
• Develop, implement, and refine analytical algorithms to improve performance and mission outcomes
• Perform data curation, normalization, transformation, and integration across multiple data sources
• Design and build automated data processing pipelines and reproducible analytics workflows
• Conduct exploratory data analysis, hypothesis testing, and statistical modeling
• Develop models for inference, prediction, and domain-specific analytics
• Create data visualizations to effectively communicate analytical results
• Translate mission requirements into technical data solutions and analytical workflows
• Communicate findings and recommendations to both technical and non-technical stakeholders
• Collaborate with analysts, engineers, and mission partners to support cyber and mission objectives
• Strong experience in data science, machine learning, and statistical analysis
• Proficiency in Python and experience working in data analysis environments (e.g., Jupyter Notebooks)
• Experience working with large-scale data and Big Data platforms (e.g., Spark or similar technologies)