Northrop Grumman Australia · 21 hours ago
Sr. Principal Data Scientist - Machine Learning Engineer
United States-Virginia-Unknown City
Full-time
Hybrid
Senior Level, Lead/Staff
$142K/yr - $213K/yr
4+ years expNorthrop Grumman is a leading technology company that provides innovative solutions impacting lives globally. They are seeking a Sr. Principal Data Scientist / Machine Learning Engineer to build user-friendly, production-grade ML/AI applications and develop cloud-based infrastructure to support data analytics workflows.
Defense & Space
Responsibilities
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 CloudFormation), 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
Qualification
Required
Must have a PhD with 4 years of relevant professional experience OR a Master's degree with 6 years of relevant professional experience OR Bachelor's degree with 8 years of relevant professional experience
Must have strong proficiency with Python, SQL, and Git
Must have experience with frameworks for rapid application development (e.g., Streamlit, Gradio, Starlette, Next.js)
Must have knowledge of DevOps or MLOps concepts and their application in data science workflows
Must have strong understanding of containerization (e.g., Docker, Podman)
Must have the ability to work collaboratively with data teams (data scientists, analysts) to support analytics workflows and insights
Must have demonstrated problem-solving and critical-thinking skills with an ability to handle complex technical challenges
Must have excellent communication skills and comfort engaging with non-technical stakeholders
Preferred
Proven track record of deploying and monitoring production-grade software systems on AWS
Experience with Databricks and PySpark for data transformation and analytics
Proven experience building and deploying web-based visualization or decision-support tools for business use cases
Exposure to workflow orchestration tools (e.g., AWS Step Functions, Apache Airflow) and infrastructure-as-code tools (e.g., Terraform, AWS CloudFormation)
Familiarity with scalable data architectures and machine learning deployment frameworks
Domain experience in manufacturing analytics, operations research, supply chain optimization, or financial forecasting
Background in consulting, forward-deployed engineering, or other client-facing technical roles where you translated ambiguous business problems into technical solutions
Benefits
Health insurance coverage
Life and disability insurance
Savings plan
Company paid holidays
Paid time off (PTO) for vacation and/or personal business
Company
Northrop Grumman Australia
Northrop Grumman Australia is the Australia-based arm of Northrop Grumman Corporation and committed to generating long-term prosperity, investing in advanced Research & Development, sovereign and exportable Intellectual Property, high-quality jobs and long-term technology leadership across the Commonwealth.
501-1000 employees
Funding
Current Stage
Late StageCompany data provided by crunchbase