Principal Data Scientist Insights & Intelligence

Northrop Grumman's Insights & Intelligence division is recruiting a Principal Data Scientist to drive analytical programs and deliver production-grade data science solutions that inform engineers, program managers, and leaders. This remote-hybrid role emphasizes translating business challenges into rigorous analytics and strategic insights across the organization.

Responsibilities

• Collaborate with engineers, program managers, and subject-matter experts to scope problems, frame the right analytical questions, and translate business needs into robust data science strategies
• Break down complex problems with critical thinking, evaluate data quality and relevance, challenge assumptions, and design methods that address the business objective
• Develop statistical models, machine learning solutions, and analytical frameworks that yield actionable insights and guide operational decisions
• Build user-friendly, production-ready ML/AI applications (for example Streamlit, Dash) and analytic artifacts that deliver insights to teams across the enterprise
• Write production-grade Python code and assemble analytics pipelines on cloud platforms (AWS, Databricks) to support scalable, reproducible workflows
• Deliver insights through executive recommendations, analytical reports, interactive dashboards, and direct discussions with business leaders
• Own the technical quality and business impact of your work by making thoughtful methodological choices, validating approaches, and standing behind recommendations
• Stay current on analytical methods, statistical techniques, and domain-specific best practices to continually improve quality and impact

Requirements

• At least five years of hands-on experience in data science, data analysis, or related professional roles
• Strong proficiency with Python, SQL, and Git
• Solid understanding of statistical methods, machine learning algorithms, and selecting appropriate analytical techniques
• Experience developing and deploying machine learning models in production environments
• Proven ability to translate complex business problems into rigorous analytical frameworks
• Demonstrated problem-solving and critical-thinking skills to tackle complex analytical challenges
• Excellent communication skills with the ability to present actionable recommendations to non-technical stakeholders
• Proven ownership and accountability for technical decisions and project outcomes

Technologies

• Python
• SQL
• Git
• Streamlit
• Dash
• AWS
• Databricks
• PySpark
• Docker

Benefits

• Health insurance coverage
• Life and disability insurance
• Savings plan
• Company paid holidays
• Paid time off for vacation and/or personal matters
• Overtime eligibility
• Shift differential eligibility
• Discretionary bonus
• Annual bonuses
• Long-term incentives

Relocation assistance

No relocation assistance available

Clearance required for start

None

Clearance type

None

Travel

Yes, 10% of the time

Work arrangement

This is a hybrid/remote role. The majority of the team is based in the Northern Virginia area, but the organization operates primarily remotely and values flexibility. The standard schedule is a 9/80, with nine-hour days Monday through Thursday and every other Friday off.

Salary

USD 113,900.00 - 170,900.00 per year

Location

Remote (hybrid)

Preferred qualifications

• Experience with AWS and Databricks for data processing and model development
• Experience with PySpark for large-scale data transformation and analytics
• Proven experience building and deploying web-based visualization or decision-support tools (Streamlit, Dash)
• Knowledge of MLOps concepts and best practices for deploying models to production
• Understanding of containerization and cloud-based deployment
• Familiarity with advanced analytical techniques such as causal inference, experimental design, time series forecasting, optimization, or Bayesian methods
• Domain experience in program management, business management, operations research, earned value management, or financial forecasting
• Background in consulting or client-facing technical roles where ambiguous business problems were translated into technical solutions