Data Science AI/ML Engineer

4 weeks ago


Weatherford, United States Impac Exploration Services Inc Full time
Job DescriptionJob Description

Job Description: As an integral part of our organization, you will contribute to the development and implementation of cutting-edge machine learning and artificial intelligence solutions. You will collaborate with cross-functional teams across our organization to solve complex problems and drive innovation.

Responsibilities:

  • Conduct exploratory data analysis to uncover insights and trends
  • Develop and implement machine learning models using Python and relevant libraries
  • Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions
  • Participate in the deployment of models into production environments
  • Stay up-to-date with the latest advancements in data science and machine learning
  • Properly document code, track and monitor experiments, and build necessary repositories

Qualifications:

  • Pursuing a Master's or PhD degree in Computer Science, Statistics, Mathematics, or a related field. In lieu of a degree, a proven track record of innovative projects or research in the field of ML/AI
  • Strong foundation in data structures, algorithms, and statistics
  • Proficiency in Python programming and data analysis libraries
  • Experience with machine learning frameworks and libraries
  • Excellent problem-solving and analytical skills
  • Strong communication and interpersonal skills

Preferred Qualifications:

  • Familiarity with cloud platforms (AWS, GCP, Azure)
  • Experience with big data technologies (Hadoop, Spark)
  • Knowledge of the geosciences, energy, or oil and gas industries

Benefits:

  • Opportunity to work on real-world projects with a significant impact
  • Fully remote (with opportunity for on-site visits to our offices, labs and field locations)
  • Encouraged to take advantage of opportunities for professional development, networking, authoring abstracts and research papers, and engagement with the broader data science community


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