At Northrop Grumman, the Insights & Intelligence (i2) organization seeks to embed trusted AI and data insights into every business decision at the company. Our Program Management i2 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:
oWork directly with stakeholders (engineers, program managers, subject matter experts) to scope problems, identify constraints, and iterate on technical solutions
oBridge analytics and infrastructure by understanding both the business problem and the approach, then building systems that deliver insights
oBuild 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
oDevelop and maintain cloud‑based infrastructure (AWS, Databricks) and tooling to support scalable and reliable data analytics workflows
oDesign and implement CI/CD pipelines, infrastructure‑as‑code (Terraform, AWS CloudFormation), and MLOps practices that enhance team productivity
oOptimize existing workflows and advocate for software engineering best practices (version control, modular design, testing) to drive team efficiency and code quality
oStay current on cloud technologies, MLOps trends, and application frameworks to identify opportunities for improvement
What Makes You Successful in this role:
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.
Work Arrangement
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.
Basic Qualifications:
oMust 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
oMust have strong proficiency with Python, SQL, and Git
oMust have experience with frameworks for rapid application development (e.g., Streamlit, Gradio, Starlette, Next.js)
oMust have knowledge of DevOps or MLOps concepts and their application in data science workflows
oMust have strong understanding of containerization (e.g., Docker, Podman)
oMust have the ability to work collaboratively with data teams (data scientists, analysts) to support analytics workflows and insights
oMust have demonstrated problem‑solving and critical‑thinking skills with an ability to handle complex technical challenges
oMust have excellent communication skills and comfort engaging with non‑technical stakeholders
Preferred Qualifications:
oProven track record of deploying and monitoring production‑grade software systems on AWS
oExperience with Databricks and PySpark for data transformation and analytics
oProven experience building and deploying web‑based visualization or decision‑support tools for business use cases
oExposure to workflow orchestration tools (e.g., AWS Step Functions, Apache Airflow) and infrastructure‑as‑code tools (e.g., Terraform, AWS CloudFormation)
oFamiliarity with scalable data architectures and machine learning deployment frameworks
oDomain experience in program management, business management, operations research, earned value management, or financial forecasting
oBackground in consulting, forward‑deployed engineering, or other client‑facing technical roles where you translated ambiguous business problems into technical solutions
Primary Level Salary Range: $142,200.00 - $213,200.00The above salary range represents a general guideline; however, Northrop Grumman considers a number of factors when determining base salary offers such as the scope and responsibilities of the position and the candidate's experience, education, skills and current market conditions.Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay. 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. In addition, Northrop Grumman provides a variety of benefits including health insurance coverage, life and disability insurance, savings plan, Company paid holidays and paid time off (PTO) for vacation and/or personal business.The application period for the job is estimated to be 20 days from the job posting date. However, this timeline may be shortened or extended depending on business needs and the availability of qualified candidates.Northrop Grumman is an Equal Opportunity Employer, making decisions without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital statu