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Data Scientist/Machine Learning Engineer

ДТЭК, ООО, энергетическая компания


branchЭнергетика и Энергоносители



contactИванова Снежана


  • полная занятость
  • английский

Особенности вакансии


Senior/Старший специалист

Вид занятости

Полная занятость

Знание языка

Английский язык

Язык программирования



R language


  • Establish a network of contacts to be able to solve tasks of any complexity.
  • Research, design, and prototype robust and scalable models based on machine learning, data mining, and statistical modeling to answer key business problems.
  • Build tools and support structures needed to analyze data, perform elements of data cleaning, feature selection, and feature engineering and organize experiments in conjunction with best practices.
  • Present findings to stakeholders to drive improvements and solutions from concept through to delivery.
  • Keep abreast of the latest developments in the field by continuous learning and proactively champion promising new methods relevant to the problems at hand.

Preferred Qualifications:

  • PhD in computer science, computer engineering or MS with 5+ years of experience in related field.
  • Demonstrated history of driving and delivering analytics models and solutions.
  • Deep knowledge of fundamentals of machine learning, data mining, and statistical predictive modeling, and extensive experience applying these methods to real-world problems.
  • Strong skills in software prototyping and engineering with expertise in applicable programming and analytics languages (Python, R, C/C++) and various open source machine learning and analytics packages to generate deliverable modules and prototype demonstrations of their work.
  • The breadth of skills and experience in machine learning - diverse types of data, diverse data sources, different types of learning models, diverse learning settings.
  • Demonstrated ability to propose novel solutions to problems, performing experiments to show the feasibility of their solutions and working to refine the solutions into a real-world contex



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