Location: Copenhagen, Denmark (On-site, 1 day per week flexibility to work from home)
Salary / Hourly Rate: $160,000 - $180,000 per year
Benefits: Company paid pension (5%),30 days of holiday + bank holidays,Loads of social events, wellbeing initiatives and great food,Bonus: 1 month of salary based on company trading profits, paid out at the end of the year,For candidates who're relocating, we would offer services from a mobility company called Relocation Scandinavia, as well as 1 additional month of salary (paid out on the first payslip). The mobility company would assist with practicalities, processing work permit and finding an apartment
Role Information
Role Overview: N/A
Responsibilities: Design and implement advanced predictive models to forecast energy market trends and inform trading strategies., Build, curate, and maintain high-quality datasets by integrating diverse energy market data sources, including fundamental and real-time market inputs., Conduct in-depth research and analysis of energy market dynamics to support model development., Develop, test, and deploy production-level code for trading systems, predictive tools, and data pipelines., Optimize algorithms, models, and datasets for performance, accuracy, and scalability., Collaborate with the team to share insights and refine strategies, while owning your individual projects.
Qualifications: Advanced degree (PhD preferred) in a quantitative field (e.g., Mathematics, Physics, Computer Science, Engineering, or similar)., Hands-on experience in power or gas markets, or in forecasting key energy fundamentals such as solar and wind power production or demand., Expertise in predictive modelling, with a track record of developing accurate forecasting tools for financial or energy markets., Strong skills in building and managing complex datasets, including data sourcing, cleaning, and structuring for analysis., Advanced programming skills in Python, C++, and/or C#, with a focus on clean, efficient, and reliable code., Solid background in computer science and software development, including data structures, algorithms, and system design., Passion for computers and technology, with a proactive approach to learning and problem-solving., Ability to work independently in a fast-paced environment while delivering high-quality results., Excellent analytical skills and a rigorous approach to modelling, research, and data validation., Experience with large-scale data analysis or machine learning applications in trading.
Minimum Requirements: PhD would be preferred, not a strict requirement,No strict rule on academic institutions - but they need to be good universities (at least top 100) (https://www.timeshighereducation.com/world-university-rankings/2026/subject-ranking/computer-science),Energy domain experience is a must for this particular role, ideal level is from 2-5 years.
Screening Questions: N/A
Company Information
About Company: N/A
Culture: N/A
Additional Information
Interview Process: Technical test to start via CoderPad (test is focused on programming and infrastructure skills), 1st interview - 90 minutes with 2 team members (covers highlights on a past project they feel is relevant to talk about, additional screening on programming/computer science fundamentals skills and overall role fit), Final interview - Workday here at Alipes, full day. We will cover travel costs if they are outside DK. This will be working on a relevant task throughout the day and meeting with different team members. If they are based in Denmark, we will compensate them for the day (DKK 3500).
Day to day: Model Architecture: Design and refine predictive models using time-series analysis and machine learning ensembles to forecast price volatility and grid imbalances., Data Pipeline Engineering: Build and maintain high-performance data architectures in Python or C++ to integrate weather forecasts, transmission constraints, and real-time exchange feeds., Backtesting & Validation: Run large-scale simulations against historical data to validate hypotheses, accounting for slippage, transaction costs, and execution latency., Production Deployment: Develop and optimize production-level code for computational efficiency, ensuring models can handle high-velocity data throughput for automated execution., Quantitative Market Analysis: Translate physical market insights, such as renewable penetration and cross-border flows, into mathematical features that enhance model accuracy., Collaborative Technical Review: Participate in rigorous peer reviews of code and mathematical proofs with a team of PhD quants to ensure infrastructure scalability and identify edge cases., Performance Optimization: Monitor live model performance to identify predictive drift, diagnosing root causes and implementing rapid iterations to maintain the firm's competitive edge.
Team: The quants report to the Head of Energy Quant, who reports to the CEO of Alipes Capital
Growth: Growth opportunities are dependent on how the individual develops and performs. We don't have a structured career ladder or similar, but in general our teams have autonomy and quants can dive into areas they find interesting. If we continue growing there may be opportunities for leading a team in the future.
Ideal Candidate Profile: The role requires a very high level of computer science fundamentals/hacking/programming skills, along with general mathematical modelling experience and domain background within Energy. Strong CS/Programming skills would take precedent over level of modelling skills, but they will need both to pass the interview process.
