Our client is a growing organization that is at the forefront of innovation in the energy trading industry. As a Weather Data Scientist, you will work with advanced science and technology to provide new insights and forecasts that shape the company's trading practices. You will be responsible for analyzing large amounts of weather data, developing predictive models, and designing strategies that create value and mitigate risk.
- Building advanced weather-related forecasting models to predict energy demand and renewable production and energy flow.
- Incorporating advanced meteorological knowledge to develop novel features that will feed into the machine learning models.
- Researching and developing machine learning-based methods for short-term weather forecasting and nowcasting.
- Coming up with new approaches for handling and analyzing atmospheric model output data.
- Collaborating with other data scientists and machine learning engineers to contribute to building an in-house forecasting framework.
- A master's or doctoral degree in Meteorology, Atmospheric Science, or a related field.
- Comprehensive understanding of at least one of the following: numerical weather prediction, nowcasting/short-near term weather prediction, energy-related time series forecasting.
- Experience working with models like ECMWF, GFS, and/or post-processing their output.
- Excellent Python coding skills for data analysis and model building.
- Experience in machine learning, particularly applied to weather forecasting or energy fundamentals (wind, solar, hydro, etc.) prediction.
- Familiarity with production-grade software engineering best practices (Git, bash, Docker) or willingness to familiarize yourself with these topics.
- Excellent research skills and the ability to test and discover new ideas.
- Excellent communication skills to clearly and effectively communicate with data scientists, engineers, and business stakeholders.
- At least 2-3 years of relevant experience in a similar role in the industry.
- Experience in advanced machine learning methods like deep learning or graph neural networks is a plus.
- Familiarity with object-oriented programming (OOP) is desirable.
If you are a highly motivated and innovative individual who is passionate about using technology and data to make a difference in the energy trading industry, we want to hear from you.