Job Description Summary

Enterprise Optimization Research Scientist role is part of Enterprise Optimization Research lab within GE Aerospace Research Digital and Electrical Systems organization. As an Enterprise Optimization Researcher you will have the opportunity to work in multi-disciplinary research teams and develop and apply robust algorithms to enhance system performance of large complex systems driven by GE Aerospace and US Government technology needs. Candidates for this role should have strong theoretical background on algorithm development and have strong interest to learn deploying algorithms in scalable cloud and distributed computing environments within enterprise systems.

Job Description

• Handling high-frequency multimodal data from distributed, heterogeneous information systems
• Developing and testing algorithms within cloud-computing frameworks that solve large-scale problems
• Code quick prototype analytics tools for early phase of software systems production
• Contribute to development and writing of internal and external proposals
• Patenting your inventions and develop a record of publication via conferences and peer reviewed journals
• Research and develop tools, frameworks and processes to improve analytical methods, performance, scale and sophistication of algorithms and systems applications
• Clearly and professionally communicate progress and results of your research with the team, business leaders, customers and technology providers
• Working closely with project leaders and principal investigators to meet project deliverables.
• The employee is expected to work independently as part of project teams.

• PhD in Computer Science/Engineering, Applied Mathematics, Optimization, Statistics or closely related field OR MS Computer Science/Engineering, Applied Mathematics, Optimization, Statistics or closely related field with minimum of 3 years of professional experience in an industrial setting
• Strong data handling skills such as acquiring, cleaning, and organizing large multimodal data sets, feature engineering to identify influential predictors, and using analytics to design and improve decision support system(s) in distributed and high-performance computing infrastructures
• Fast learning capabilities for new tools, programming environments and analytical methods
• Demonstrated development skills and documentation capability in Python, R, (Java, C++ is a plus) etc. in IDEs for the integration of analytical models into middleware and data bases
• Demonstrated capability to rapidly develop prototypes of assets being used in processes, connecting assumption and real-time data, post processing analytics and decision-support systems
• Legal authorization to work in the U.S. is required. We will not sponsor individuals at the Masters' level for employment visas, now or in the future, for this job opening
• Must be willing to work out of an office located in Niskayuna, NY
• Because of the specific categories of data handled by GE Aerospace Research and the structure of our work environment, we are unable to accommodate employment of persons while they are considered nationals of embargoed countries subject to restriction under the US Export Administration Regulations (EAR), 15 CFR Section 746 et seq. (currently North Korea, Syria, Iran and Cuba). Please note that citizens of embargoed countries who have either "U.S. person" status under U.S. export control laws or subsequent citizenship from a non-embargoed country can be considered

• In-depth theoretical knowledge in one or more of the following areas:
  Statistical Learning, complexity theory, approximation algorithms, machine learning, combinatorial optimization, reinforcement learning
• Experience in designing algorithms in large complex systems
• Experience in designing standards and workflows for data ingestion, validation and calibration
• Experience in full-stack software development
• Ability to connect learning from past academic environment to industrial research environment. Strong desire to solve complex, real-world problems with ability to develop and validate solutions to narrowly defined technical challenges.
• Excellent written and oral communication skills and effective interpersonal skills
• Ability to adapt and thrive in a dynamic, outcome-focused industrial research environment
• Self-motivated and ability to work independently and as part of a team with minimal guidance.