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