The Sr. Staff Data Scientist will be part of Power Digital Data Science & Analytics team as technical domain expert addressing machine learning, data science and analytics needs in a commercial technology and product development environment.
In this role, you will contribute to the design, development and deployment of modern machine learning, data science, and analytics methods for power generation, transmission and distribution domains.
As a Sr. Staff Data Scientist, you will be part of teams on commercially facing product development initiatives, typically involving domain and system understanding, large and complex data sets from multiple sources. These teams typically include data scientists, analytics engineers, data engineers, software developers, product managers, program managers and end users, working in concert with partners in GE Power and Digital businesses. Potential applications areas include asset performance management, asset monitoring and diagnostics, operations optimization, network level optimization, energy orchestration, outage response, risk assessment etc.
Lead accelerated NPI and customer funded development of physics aided AI and Machine Learning driven software solutions for Power Generation, Transmission & Distribution (T&D) product suites
Demonstrate solid engineering and domain knowledge in delivering innovative advanced analytics based solutions for power customers
Engage key technical & subject matter experts (SMEs) across the Power business for knowledge capture into the solutions. And work with Product Management, Software Engineering and UX design teams to develop, verify, and validate analytics to address customer needs and opportunities across digital energy value chain
Demonstrate technical leadership in building foundation for AI and Machine Learning for Power Generation, Transmission and Distribution analytics use cases
Collaborate across Power and Digital businesses to build differentiated solutions that fit the design and future of Power Generation and T&D products
Lead a team of Analytics Engineers and Data Scientists for development, deployment, and application of applied analytics, predictive analytics and prescriptive analytics
Work as part of a cross-functional team to translate algorithms into commercially viable products and services.
Foster an environment that encourages innovation, creative risk taking, speed and agility.
Work with data engineers on data quality assessment, data cleansing and data analytics
Apply a structured process to design and build new analytic packages and contribute to build out of most comprehensive Analytics Catalog for Power business
Contribute to technology forecasting and IP strategies to the business Qualifications/Requirements:
Master's degree in a “STEM” major (Science, Technology, Engineering, Mathematics) plus 9 years analytics development for industrial applications in a commercial/industrial setting OR Ph.D. in a “STEM” major (Science, Technology, Engineering, Mathematics) plus 7 year analytics development for industrial applications in a commercial/industrial setting
Legal authorization to work in the U.S. is required. We will not sponsor individuals for employment visas, now or in the future, for this job
Must be willing to work out of an office located in San Ramon, CA or Atlanta, GA
Must be willing to travel to other GE and customer sites as required with < 10% travel anticipated Desired Characteristics:
Minimum of 5 years of engineering experience in hands on implementation of Data Science and Analytics/ AI & ML techniques for industrial applications
Demonstrated expertise in the use of one or more of latest analytic software tools or packages (e.g., Python, R, SAS, JMP, SPSS etc.). Programming experience with open source scripting and other data analysis packages
Demonstrated expertise in data visualization and storytelling to translate complex data into customer insights
Demonstrated expertise in data modeling, feature engineering, and the development and application of descriptive, applied, and predictive analytics on industrial datasets
Demonstrated expertise in data science methodologies technology and industry trends
Strong analytics skills with expertise in machine learning, statistical analysis, signal processing and data mining. Demonstrated skill in prescriptive analytics and analytic productization
Understanding of industrial equipment, processes and energy network operations, especially in the areas of power plants, transmission & distribution domain
Hands on experience with data management methods, analytics deployment and orchestration tools, database technologies and visualization tools for customer facing software applications
Proven track record of Innovation and IP generation
Domain expertise in power generation, transmission & distribution space with broad understanding of energy products and services
Proactively engages with cross-functional teams to resolve issues and design solutions using critical thinking and analytics skills and best practices by actively incorporating input from various sources
GE (NYSE:GE) drives the world forward by tackling its biggest challenges. By combining world-class engineering with software and analytics, GE helps the world work more efficiently, reliably, and safely. GE people are global, diverse and dedicated, operating with the highest integrity and passion to fulfill GE's mission and deliver for our customers. www.ge.com GE offers a great work environment, professional development, challenging careers, and competitive compensation. GE is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, gender (including pregnancy), sexual orientation, gender identity or expression, age, disability, veteran status or any other characteristics protected by law.
Additional Eligibility Qualifications: GE will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable). Additional Locations: United States;California, Georgia;San Ramon, Atlanta;