Machine Learning Weather Researcher
Imagine working with cutting-edge machine learning models, crunching high frequency data sets and sparring with exceptional and fun colleagues, all while taking part in scaling our business even further. Does this sound highly appealing to you?
Then you might be our new Machine Learning (ML) Weather Researcher at Alipes Capital.
About the Role
Alipes began trading in the Energy sector in 2022. We use machine learning technology for reading and interpreting fundamental and market data and execute our trading strategies based on this data. Since our inception in 2008, we have continuously grown and diversified into new business areas driven by our technology. Alipes aims to support liquid power markets and free flow of energy, which are critical to facilitate the transition from fossil fuels to renewable energy sources, thereby promoting a sustainable future.
Forecasting power generation from renewables is crucial for price discovery, risk management and for balancing the power grid. Recent advances in ML/AI/Neural based weather modeling promise models which are orders of magnitude faster to run than traditional physics-based numerical weather models.
Your work as our new ML Weather Researcher 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.
You will get instant validation of your work and experience short feedback cycles, where going from inception to deployment can be a matter of hours. There will be no red tape to cut and no sales people to consult. We are centrally located in Copenhagen and have 55 bright and ambitious team members.
About the Team
All of this will happen in an informal atmosphere where technical discussions are valued, and you are encouraged to take ownership of, and pride in, your work. You will impact the direction of the team, prioritize your work and choose the tools that get the job done. We are 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. We enjoy collaboration and are always willing to lend a helping hand. We are working alongside two other teams of software developers and economists that implement and conceive the mathematical models together with us. What makes this constellation work great is that all of the individual team members write code and understand that a seemingly trivial change can actually require a lot of work, and vice versa.
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
What we can Offer You
- 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 central Copenhagen with a hybrid work model
- Pension, Health Insurance and 30 days of vacation
Practicalities
To apply, please send us your CV and a cover letter telling us why you think this role is a great fit for you. If your profile looks like a good match, we will get in touch to coordinate an online technical test as a first step in the interview process.
- Department
- Quant
- Locations
- Copenhagen
Copenhagen
About Alipes
We are on a mission to automate the financial and energy markets while focusing on making complex decisions faster than anyone else. Every tick counts for victory!
Based in Copenhagen, we pride ourselves to continuously solve challenging problems in order to swiftly navigate the currents of international financial and energy markets. We value the aptitude, collaboration and scientific approach of our dedicated employees. In the end, our teams are the primary resource, so we do our best to create a workplace with room for creativity and intellectual challenges.
Machine Learning Weather Researcher
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