Sr. Staff Data Scientist leading technology initiatives for advanced manufacturing at Northrop Grumman. Developing architectures for digital technologies and providing technical leadership in engineering solutions.
Responsibilities
Provide leadership/direction to ensure technology initiatives and opportunities for process improvements are systematically identified, pursued, and supported.
Develop architectures and concepts for advanced digital technologies with a focus on implementation within Northrop Grumman
Interact with customers (internal and external)
Reach out and work with colleges, universities, government, suppliers as part of development and improvement projects
Introduce and develop new technologies for the manufacturing floor
Lead projects consisting of cross functional teams of high performing engineers developing advanced systems designs and concepts.
Provide technical leadership and oversight to achieve efficient, effective, and innovative Engineering solutions
Apply new technologies as well as common designs and products enabling rapid development, prototyping and affordable solutions.
Requirements
Bachelor of Science degree in a Science, Technology, Engineering or Mathematics (STEM) discipline from an accredited university with 14 years of experience in engineering; OR Master of Science degree in a STEM discipline from an accredited university with 12 years of experience in engineering; OR PhD in a STEM discipline from an accredited university with 10 years of experience in engineering.
Secret Clearance
Knowledge of data gathering, cleansing and transformation techniques
Experience with common data science toolkits/languages such as python/R, scikit-learn, PyTorch/TensorFlow, matplotlib, numpy, C++ or python
Exceptional analytical skills.
Familiarity with cloud
Knowledge and experience performing model uncertainty analysis, error modelling, and/or error propagation.
Knowledge of best practices in data analysis.
Excellent interpersonal and communication skills.
Experience developing mathematical models of dynamic systems from first principles.
Knowledge and experience with System Identification techniques using statistical methods to validate dynamic system models with test data.
Experience performing parametric and non-parametric system identification.
Experience with data acquisition systems and/or post-processing experimental test data.
Documenting processes and maintaining data records.
Benefits
Health insurance coverage
Life and disability insurance
Savings plan
Company paid holidays
Paid time off (PTO) for vacation and/or personal business
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