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Principal Data Scientist Insights & Intelligence

Northrop Grumman Remote 🌍 Remote

Remote

Today

$114k - $171k/yr Full time Analytics Artificial Intelligence Big Data

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Job Description

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

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