Data Scientist

3 weeks ago

Sugar Land, United States Schlumberger Full time
The Data Scientist is responsible for conducting undirected research and tackle open-ended data problems and questions. Drawing on an advanced degree in a quantitative field such as computer science, physics, statistics or applied mathematics, the Data Scientist demonstrates the knowledge to invent new algorithms to solve data problems.
  • Research and assess next-generation technologies for machinery diagnostics and prognostics and data-driven modeling and optimization of complex systems. Demonstrate advanced working knowledge and experience with machine learning algorithms and population-based meta-heuristic optimization methods.
  • Generate innovative ideas, establish new research directions, and shape and execute on technical projects.
  • Maintain state-of-the-art knowledge and contribute to technical discussions and reviews as an expert in related areas of responsibility.
  • Apply theoretical knowledge to solve industrial problems.
  • Apply engineering knowledge in developing data-driven algorithms for anomaly detection, failure prediction and optimization.
  • Collaborate with field and product engineers to identify key health monitoring parameters of a system.
  • Process large multivariate data sets collected from equipment operations, manufacturing tests and diagnostic routines.
  • Communicate ideas, plans and results effectively via oral and written reports.

  • PhD in Computer Science, Statistics, Electrical Engineering, Applied Mathematics, Computational Physics/Chemistry/Biology, or a highly quantitative discipline with a minimum of three years' experience, or,
  • Master's degree in Computer Science, Electrical Engineering, Mathematics/Statistics, with a minimum of seven years of AI-related experience
  • 3 years of professional experience in Data Analytics, Machine-Learning, and/or computational physics.
  • Evidence of proficiency in programming
  • Strong oral and written communication skills
  • Ability to work independently and in a team of scientists and engineers

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