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