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Role Summary: The person will be part of the core Data Sciences team at GE Oil & Gas Engineering and develops analytics to meet objectives of the business. In this role, you will lead the development and deployment of modern machine learning, and statistical methods for finding process insights to problems in Oil & Gas
Essential Responsibilities: As a Sr. Data Scientist, you will be part of a cross-disciplinary modeling & data science team on commercially-facing development projects, typically involving large, complex data sets. These teams typically include domain experts, statisticians, computer scientists, software developers, engineers, product managers, and end users, working in concert with partners in GE Oil & Gas business units. Potential application areas include remote monitoring and diagnostics across Oil & Gas infrastructure and industrial sectors, and operations optimization.
In the role of Senior Data Scientist you will:
Data exploration and model building targeting given CTQs (field issue investigations, developing tracking filters, inspections, root cause analysis, etc.)
Understand correlation between various process parameters and provide insights into data
Execute design, analysis and development of assigned projects adhering to business standards, practices, procedures and product / program requirements
Work alongside software developers and software engineers to translate algorithms into commercially viable products and services
Work in technical teams in development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics
Leverage existing Oil & Gas teams, and collaborate with GE Software and Global Research
Communicate results, findings and observations in clear and concise documents (presentations, reports, technical articles) to peers and program leader in formal / informal reviews
Document technical data generated by the assigned project consistent with engineering policies and procedures
Effective multitasking and delivery on time with quality
Participate on teams assigned to address organizational initiatives
Guide young engineers
Master's Degree in Statistics, Computer Science, Mechanical or Chemical or Electrical Engineering from an accredited college or university
Minimum 6 years of experience in analytics development for industrial applications in a commercial / industrial setting
Ph.D. in a STEM’ field (Science, Technology, Engineering, Math) from an accredited college or university with a minimum 3 year of experience in analytics development for industrial
Hands-on experience with projects involving Exploratory Data analysis, Model building, Model assessment, Pattern Recognition, machine learning
Hands-on experience in information retrieval, architecture involving handling large volumes of data
Demonstrated skill in the use of one or more analytic software tools or languages (e.g., SAS, SPSS, R, Python)
Oil & Gas domain knowledge and experience in either upstream, midstream or downstream segments
Experience with end-to-end modeling projects, from research to solutions to analytic products
Strong hands-on skills in sourcing, cleaning, manipulating and analyzing large volumes of data
Strong oral and written communication skills
Strong interpersonal and leadership skills and ability to influence others and lead small teams
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