Sr. Principal Data Scientist - Machine Learning Engineer

RELOCATION ASSISTANCE:
No relocation assistance available

CLEARANCE TYPE:
None

TRAVEL:
Yes, 10% of the Time

At Northrop Grumman, our employees have incredible opportunities to work on revolutionary systems that impact people’s lives around the world today, and for generations to come. Our pioneering and inventive spirit has enabled us to be at the forefront of many technological advancements in our nation's history - from the first flight across the Atlantic Ocean, to stealth bombers, to landing on the moon.

We look for people who have bold new ideas, courage and a pioneering spirit to join forces to invent the future, and have fun along the way. Our culture thrives on intellectual curiosity, cognitive diversity and bringing your whole self to work — and we have an insatiable drive to do what others think is impossible. Our employees are not only part of history, they’re making history.

At Northrop Grumman, the Insights & Intelligence (i2) organization seeks to embed trusted AI and data insights into every business decision at the company. Our Applied Data Science &AI team builds 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 data scientist / machine learning engineer, you will be a technical force multiplier—working with program teams to understand their challenges, building the infrastructure and applications to address them, and deploying production solutions that drive high-impact decisions.

Job duties include, but are not limited to:

• Work directly with stakeholders (engineers, program managers, subject matter experts) to scope problems, identify constraints, and iterate on technical solutions

• Bridge analytics and infrastructure by understanding both the business problem and the approach, then building systems that deliver insights

• Build user‑friendly, production‑grade ML/AI applications (e.g., Streamlit, Gradio) that provide data insights to teams across the enterprise and enable better decision making

• Develop and maintain cloud‑based infrastructure (AWS, Databricks) and tooling to support scalable and reliable data analytics workflows

• Design and implement CI/CD pipelines, infrastructure‑as‑code (Terraform, AWS Cloud Formation), and MLOps practices that enhance team productivity

• Optimize existing workflows and advocate for software engineering best practices (version control, modular design, testing) to drive team efficiency and code quality

• Stay current on cloud technologies, MLOps trends, and application frameworks to identify opportunities for improvement

You balance speed with quality: You can assess when “good enough now” beats “perfect later” and prioritize impact and working solutions over perfection.

You have high agency: You proactively gather information, identify blockers, can operate in ambiguity, and make thoughtful decisions with incomplete information.

You’re technically versatile: You’re comfortable diving into infrastructure one day and analyzing a dataset the next, stepping into different roles depending on project needs.

You’re a bridge ‑ builder: You can talk to data scientists about model deployment, engineers about infrastructure, and business stakeholders about their problem. You translate and collaborate across domains.

This is a hybrid/remote position. Most of our team is based in the Northern Virginia area, and we welcome candidates who can sometimes collaborate in person, but we operate primarily remotely and value flexibility. This position’s standard work schedule is a 9/80. The 9/80 schedule allows employees who work a nine‑hour day Monday through Thursday to take every other Friday off.

• Must have a PhD with 4 years of relevant professional experience OR…