Job description


  • Entry level
  • No Education
  • Salary to negotiate
  • Houston


Job type: Full-time
Role: Data Scientist

machine-learning, algorithm, hadoop

Job description
Our Houston Research Center focuses on research and innovation in geology, geophysics, reservoir engineering, production technology, drilling, and sensors development to advance the discovery and recovery of oil and gas. Located in Houston’s Energy Corridor, the center neighbors the nation’s leading petroleum engineering universities, labs, manufacturers, and service companies.Basic FunctionDevelop algorithms, models and prototype solutions to address challenging scientific and engineering problems for exploration and production (E&P) applications. Serve as a bridge between machine learning (ML), data science and subject matter applications.Duties & ResponsibilitiesDevelop machine learning algorithms and perform advanced statistical analyses of engineering data to obtain insights into trends and opportunitiesDevelop and maintain appropriate databasesIn close collaboration with research and business partners in the US and in the Kingdom of Saudi Arabia, offer mathematical, computational and statistical models from the collected data to automate, augment, improve or speed up human decisionsResearch and deliver proof of concepts solutions, responding to clear and specific business needsServe as a bridge between machine learning/data science and subject matter applicationsBridge the gap between prototype development and scalable production applications when neededDevelop proper unit test frameworks for artificial intelligence (AI) and ML and provides high level documentationCommunicate appropriate algorithm research and prototype development best practices back to the machine learning group, to improve learning and future capabilitiesPublish and present work in journals and at conferencesDevelop and maintain statistical reports and visual presentations for management Perform other duties and participate in special projects as assignedEducation And ExperienceBachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics & Statistics, Machine Learning and Artificial Intelligence, or Geosciences required; Master’s degree and/or Ph.D. strongly preferredMust have at least three (3) years of relevant experience in data science including at least two (2) years in AI or MLStrong fundamental understanding of various modern machine-learning methods or computational physics/geosciences/chemistry background, along with significant machine learning knowledge is desirableAbility to:compile, correlate, and compute results from large data setsdevelop machine learning algorithms and perform advanced statistical analyseseffectively collaborate with research and business partners across disciplines and culturesdemonstrate technical writing skills and develop logical and clearly defined reports and presentationsmake oral/graphic presentations to collaboration partnersshow a history of active participation in technical society activities preferredProficient with business software applications Experience in a few of the following areas: deep neural networks, reinforcement learning, Markov Random Fields, Bayesian networks, semi-supervised learning, computer vision, image processing, signal processing, distributed computing, and/or numerical optimizationSubstantial programming experience is expected, preferably in PythonExperiences with one or more of the following is highly desirable: familiarity with ML frameworks such as Tensorflow, Keras, Pytorch, MXNet, operationalizing ML models, cloud computing (e.g. Google Cloud, AWS, etc.), GPU computing environmentExperience with big-data technologies such as Hadoop/Spark is a plusExperience in oil and gas application is a plus.Must be able to comprehend and communicate accurately, clearly and concisely in EnglishNO THIRD PARTY CANDIDATES ACCEPTED

  • software