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Electricity Maps

Machine Learning Engineer, Forecasting

Fuldtid

Permanent

Njalsgade 78, 2300 København S, Danmark

SE PÅ KORT
ID: 2704034
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Indrykket for 14 dage siden

Electricity Maps’ Forecasting team’s mission is to enable our customers to leverage their flexibility to reduce carbon and cost. We’re looking for a Machine Learning Engineer to help the team expand its forecasting capabilities across signal types like carbon intensity, power production or price and across time horizons.

About you: 

  • Have a strong theoretical understanding of statistics/probability theory/optimization and at least 3 years of experience applying these concepts in a business environment.
  • Are knowledgeable about time-series models. As a bonus: you’ve worked in power forecasting or the energy sector.
  • Are comfortable integrating models into a cloud-based infrastructure that processes high volumes of data.
  • Thrive in an environment that provides autonomy, that supports your individual growth with interesting tasks.
  • Possess a pragmatic and honest communication style.
  • Are excited to work with a team with a variety of backgrounds and skill sets.

How you will contribute to our mission:

  • Improve the accuracy of our time-series models for forecasting.
  • Follow developments of the state-of-the-art for time-series forecasting, and experimenting with new model classes.
  • Contribute to the development of a fully automatic end-to-end modeling pipeline running on cloud services.
  • Promote optimization, testing and tooling for our processing pipelines.
  • Collaborate with engineers to build scalable systems.

      About us:

      • In addition to our company values, we value transparency, fairness, diversity and open communication.
      • We strive to hire brilliant people who are kind and compassionate humans.
      • We’re all co-located in Copenhagen as we value face-to-face interaction.
      • We’re accelerating our growth in the coming months/years, including potentially expanding internationally.

       Expected monthly salary for this role is DKK 48500

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