Description

  • Deployment of statistical/machine learning models using an in-house developed ML-DevOps framework
  • Origination of new data science opportunities in close collaboration with IT/Business.
  • Root Cause Analysis of subsurface production outages using causal inference & discovery methods.
  • Developing & evaluating ML solutions for predictive maintenance use cases
  • Production-level experience with core quantitative analysis techniques (e.g., predictive moClienting, machine learning, artificial intelligence, or natural language processing)
  • Quantitative background with relevant experience using data to solve problems and answer questions

Qualifications:

  • Minimum 8 years
  • Strong proficiency in Python, SQL, and experience with libraries/frameworks such as PyTorch, TensorFlow, and Scikit-learn
  • Experience with cloud and modern data science tools and platforms such as Databricks MLFlow, GCP BigQuery, AWS SageMaker, Kubeflow, and Azure ML

Mandatory Skills

  • Python, AWS, SQL, ML-DevOps, PowerBI, Data moClienting, Data science tools

Key Skills
Education

Any Gradute

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