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Job Details


Leidos

Data Scientist ( R-00067010-OTHLOC-PL-2D2165 )

Technology

Data Analyst

Yearly

No

Pittsburgh, Pennsylvania, United States

Description

Job Description:

Looking for an opportunity to make an impact?

At Leidos, we deliver innovative solutions through the efforts of our diverse and talented people who are dedicated to our customers’ success. We empower our teams, contribute to our communities, and operate sustainable. Everything we do is built on a commitment to do the right thing for our customers, our people, and our community. Our Mission, Vision, and Values guide the way we do business. Your greatest work is ahead!

An opportunity exists within the RSS Contract at National Energy Technology Laboratory (NETL)-Pittsburgh to join an interdisciplinary team participating in the research and development of advanced data analytics methods applied to energy infrastructure sensing applications, with an emphasis on natural gas infrastructure. NETL is a multi-disciplinary, scientific and technical-oriented national laboratory and the U.S. Department of Energy’s primary lab supporting fossil fuel-based energy research. The Data Scientist will collaborate on an interdisciplinary team spanning industry, academic, and national laboratory partners that seeks to develop and demonstrate advanced sensors and enabling technologies for energy infrastructure monitoring applications.

Location: 100% telework

If this sounds like the kind of environment where you can thrive, keep reading!

Primary Responsibilities Include:

  • Research within the team to identify and apply advanced data analytics methods to characterize and classify spatial, temporal, and frequency dependent features of optical fiber based distributed sensing data.
  • Utilize artificial intelligence and advanced data analytics methods for predictive monitoring of incipient failures within the natural gas infrastructure by leveraging distributed optical fiber sensing.
  • The researcher will also have opportunities to engage in data analytics for wireless sensor technology platforms and other energy infrastructure, including subsurface monitoring.
  • Develop physics-based models for understanding failures of natural gas infrastructure and for accelerated training of analytics approaches.
  • Field validation will ultimately be conducted for data collection.
  • Publications in high quality scientific peer-reviewed journals, presentations at national and international technical meetings.
  • Development of new intellectual property based on the innovative research.
  • Period status reporting and project reports (weekly/monthly/quarterly/annually) is required to update project managers and clients.
  • This position will require extensive interface with clients and potential collaborative partners, so excellent verbal and written communication skills are required.

Required Qualifications:

  • At least a M.S. degree in Statistical Methods, Mathematics, Data Science, Computer Science, Electrical Engineering, Applied Physics, Mechanical Engineering, or a related field and 2+ years of prior relevant experience.
  • Experience with development and application of advanced data analytics methods (e.g. artificial intelligence, principle component analysis, neural networks, machine learning, big data analytics) using custom developed algorithms or commercially available software packages.
  • An interest in intelligent techniques for energy infrastructure monitoring and sensing.
  • Experience with high performance computing environments, tools, and applications.
  • Excellent communication skills and a willingness and interest to collaborate in an interdisciplinary team environment to drive towards overall project and team objectives is also highly desired.

Preferred Qualifications:

  • Ph.D. degree is preferred, in Statistical Methods, Mathematics, Data Science, Computer Science, Electrical Engineering, Applied Physics, Mechanical Engineering, or a related field. Post-doctoral experience in a government-owned national laboratory is a plus.
  • Strong background in machine learning, artificial intelligence, and big data analytics applied in sensing data processing.
  • Familiar with multivariate analysis techniques for extracting information related to multiple parameters simultaneously from advanced sensing platforms.
  • Experience in advanced data analytics methods for optical fiber based distributed sensing data analysis as it relates to indicators of incipient failures and leaks within the natural gas infrastructure.
  • Knowledge of multi-physics modeling for natural gas pipeline failures.

Pay Range:Pay Range $71,500.00 - $110,000.00 - $148,500.00

#Remote