> Markdown version of [/jobs/ext/4675166-sr-principal-data-scientist-machine-learning-and-predictive-a](https://www.wearedevelopers.com/jobs/ext/4675166-sr-principal-data-scientist-machine-learning-and-predictive-a). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Principal Data Scientist - Machine Learning and Predictive A - **Company:** Northrop Grumman - **Location:** San Diego, CA, United States - **Experience:** Expert - **Salary:** $156,400 - $234,600 - **Contract:** Permanent contract - **Skills:** Data Analysis, Big Data, C++ (Programming Language), Computer Programming, Continuous Integration, Data Architecture, Information Engineering, Python (Programming Language), Machine Learning, NumPy, Azure Machine Learning, SAP (Applications), Software Engineering, SQL Databases, Pytorch, Git, Pandas, Core Data, Scikit Learn, Integration Tests, Machine Learning Operations, Hardware Infrastructure, Software Version Control, Data Pipelines, Docker - **Published:** November 11, 2026 - **Apply:** https://www.clearancejobs.com/jobs/9304313/sr-principal-data-scientist-machine-learning-and-predictive-a ## About the Role The individual we seek will be self-motivated, proactive, goal-oriented to help us grow our services, become even better at what we do and will possess the following qualifications., * Bachelor's Degree in a Science, Technology, Engineering or Mathematics discipline from an accredited university, with a minimum of 8 years of relevant experience, OR Master in STEM with 6 years of relevant experience, OR PhD/Doctorate degree in STEM with 4 years of relevant experience. * Deep understanding of Machine Learning and Deep Learning. * Recent professional experience in software development and/or data engineering. * Strong programming skills in Python and SQL. * Familiarity with CI/CD pipelines and version control (e.g., Git, Docker, etc.) * Must have the ability to obtain and maintain a US Government Top Secret clearance and Special Access Program (SAP) within a reasonable amount of time as determined by business needs., * Master's degree or higher, in Data Science or related discipline. * Experience with C/C++. * Experience with machine learning pipelines and data science workflows. * Familiarity with SQL Alchemy, Numpy, Pandas, SKLearn, PyTorch. * Ability to troubleshoot and optimize complex data queries and workflows. * Familiarity with big data concepts, machine learning pipelines, and MLOps. * Excellent problem-solving skills with the ability to troubleshoot and optimize across the entire data stack. * Ability to work in a fast-paced environment. * Current, Active, DoD Top Secret clearance. Thrive with Us ## Description Northrop Grumman is seeking an experienced, Senior Principal Data Scientist to support our Product Support Analytics and Innovation team onsite in Rancho Bernardo, California. This position is required full-time, in-office. Hybrid scheduling (time split between in-office and work-from-home) may become available depending on future project needs. Accomplish We are seeking a first-principles thinker and skilled data scientist to solve complex data challenges. This is not a role for operating pre-built tools; this is an opportunity to architect and build the core data logic of our systems. You will be responsible for creating custom, high-performance statistics and machine learning tools from the ground up, making meaning of complex data sets. Your work will involve deep data modeling, abstracting reusable patterns, and writing modular, maintainable code that stands the test of time. Essential Functions: * Collaborate closely with software engineers, analysts, and other data scientists to understand data requirements and deliver robust, integrated solutions. * Architect and develop custom, maintainable data science solutions from the ground up. * Write and maintain tests and documentation for data architecture, workflows, and processes. * Champion software engineering best practices within the data domain, including comprehensive unit/integration testing, CI/CD automation (Git, Docker), and robust documentation. * Tune and optimize complex algorithms within our on-premise infrastructure.