Quantitative Researcher for Renewable Energy
1 week ago
We're looking for an experienced Machine Learning Weather Scientist Quant to join our team in Copenhagen.
About the Role
We use machine learning technology to analyze fundamental and market data, executing our trading strategies based on this data. We've continuously grown and diversified into new business areas driven by our technology.
Our goal is to support liquid power markets and facilitate the transition from fossil fuels to renewable energy sources.
Accurate forecasting of power generation from renewables is crucial for price discovery, risk management, and balancing the power grid. Recent advances in ML/AI/Neural-based weather modeling promise models that are orders of magnitude faster to run than traditional physics-based numerical weather models.
Your work will involve turning massive data sets of weather data into machine learning models that accurately predict short-term weather patterns and power production from renewables.
About the Team
We're a tight-knit modeling team with passionate quantitative analysts covering 6 nationalities – a combination of PhD's and MSc's with expertise in statistical analysis, mathematical modeling, and machine learning.
About You
- Experience with ML/AI/Neural-based weather forecasting (GraphCast etc)
- Experience with Deep Learning and Neural Networks
- PhD or MSc degree in engineering, physics, computer science or relevant field
- Familiar with terms like ECMWF IFS, HRRR, GFS, GOES etc.
- Proficiency within computer science fundamentals, mathematics, and statistics
- Programming experience with Python, in particular data-wrangling and numerical programming
- A scientific and inquisitive mind
About Us
- Flat hierarchy and high levels of trust and autonomy
- Exciting problems to solve
- Collaborative team made up of really smart and curious people
- Nice office in Copenhagen with a hybrid work model
- Pension, Health Insurance, and 30 days of vacation
To apply, please send us your CV and a cover letter telling us why you think this role is a great fit for you.
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