Principal Data Scientist Insights & Intelligence

Northrop Grumman • New York, NY

2d • $113,900 - $170,900 • Hybrid

About The Position

At Northrop Grumman, the Insights & Intelligence (i2) organization seeks to embed trusted AI and data insights into every business decision at the company. We build lightweight, production‑grade analytics solutions that solve problems traditional enterprise tools struggle to meet. Our team operates with high autonomy, working closely with engineers and business leaders to identify high‑value problems, build apps and other products from the ground up, and deploy them into production. We value speed, intellectual curiosity, and the ability to toggle between "prototype rapidly" and "engineer for production" based on what the situation demands. As a principal data scientist, you will lead analytical projects that drive high-impact business decisions—working with program teams to deeply understand their challenges, developing rigorous analytical approaches and models, and delivering insights through production-quality code, applications, and strategic recommendations.

Requirements

• Minimum of 5 years of hands-on experience in data science, data analysis, or other relevant professional experience
• Must have strong proficiency with Python, SQL, and Git
• Must have deep understanding of statistical methods, machine learning algorithms, and when to apply different analytical techniques
• Must have experience developing and deploying machine learning models in production environments
• Must have proven ability to translate complex business problems into rigorous analytical frameworks
• Must have demonstrated problem‑solving and critical‑thinking skills with an ability to handle complex analytical challenges
• Must have excellent communication skills and ability to deliver compelling, actionable recommendations to non‑technical stakeholders
• Must have strong track record of ownership and accountability for technical decisions and project outcomes

Nice To Haves

• 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 for business use cases (e.g., Streamlit, Dash)
• Knowledge of MLOps concepts and best practices for deploying models to production
• Understanding of containerization (e.g., Docker) 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, forward‑deployed engineering, or other client‑facing technical roles where you translated ambiguous business problems into technical solutions

Responsibilities

• Work directly with stakeholders (engineers, program managers, subject matter experts) to scope problems, formulate the right analytical questions, and translate business challenges into rigorous data science approaches
• Apply deep analytical thinking to decompose complex problems—critically evaluate data quality and relevance, challenge assumptions, and design methods that address the business need
• Develop statistical models, machine learning solutions, and analytical frameworks that deliver actionable insights and drive operational decisions
• Build user‑friendly, production‑grade ML/AI applications (e.g., Streamlit, Dash) and analytical artifacts that provide data insights to teams across the enterprise and enable better decision making
• Write production-quality Python code and develop analytical pipelines using cloud-based platforms (AWS, Databricks) to support scalable and reproducible data science workflows
• Deliver insights through multiple channels—executive recommendations, analytical reports, interactive dashboards, and direct consultation with business leaders
• Take ownership of the technical quality and business impact of your work—make thoughtful methodological decisions, validate approaches rigorously, and stand behind your recommendations
• Stay current on analytical methods, statistical techniques, and domain-specific best practices to continuously improve the quality and impact of your work

Benefits

• health insurance coverage
• life and disability insurance
• savings plan
• Company paid holidays
• paid time off (PTO) for vacation and/or personal business
• Annual bonuses are designed to reward individual contributions as well as allow employees to share in company results.
• Employees in Vice President or Director positions may be eligible for Long Term Incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed