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- Tasks: Develop real-time market forecasting models for trading decisions in power markets.
- Company: Join a leading commodity trading house making waves in the energy sector.
- Benefits: Enjoy competitive pay, flexible working options, and a dynamic work environment.
- Why this job: Make a real impact with your work while collaborating with top industry professionals.
- Qualifications: Experience in energy forecasting, strong programming skills, and knowledge of power markets required.
- Other info: This role offers high-stakes decision-making opportunities in a fast-paced environment.
The predicted salary is between 43200 - 72000 £ per year.
A leading commodity trading house is seeking an exceptional data scientist to develop sophisticated real-time market forecasting models that drive trading decisions. You'll work on power market modelling across multiple time horizons, building production systems used daily by traders in electricity, gas, and related commodity markets. These aren't academic prototypes. You'll build live systems with real-time execution, mission-critical reliability and high-stakes impact. Prediction errors directly affect P&L and trading performance.
Responsibilities:
- Build production forecasting models for power markets that support real-time, high-value trading decisions.
- Develop mathematical optimisation and machine learning solutions combining multiple techniques for maximum accuracy.
- Design and maintain robust trading systems with real-time data processing and automated model updates.
Essential requirements:
- Several years' experience in energy forecasting or algorithmic trading within power markets.
- Strong mathematical optimisation, machine learning, and statistical modelling background.
- Production-level programming (Python, Java, C#).
- Experience with power market fundamentals and trading strategies.
- System architecture and platform development experience.
- Commercial awareness and stakeholder management.
Highly valued:
- Experience with power markets (day-ahead, intraday).
- Stochastic programming and optimization solvers.
- Time series forecasting and ensemble methods.
- Energy trading environment exposure.
You're likely someone who has built forecasting models for power markets at a trading house, utility, or energy consultancy. Moved beyond pure research into production system development. Strong technical skills and a clear understanding of the business impact. This is a high impact front-office role with real-time decision-making responsibility.
For a confidential discussion, please get in touch or apply with your CV.
Data Scientist - Commodities employer: Statera Talent
Contact Detail:
Statera Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Commodities
✨Tip Number 1
Familiarise yourself with the latest trends and technologies in energy forecasting and algorithmic trading. This will not only help you understand the market better but also allow you to speak confidently about your insights during interviews.
✨Tip Number 2
Network with professionals in the commodities trading sector, especially those who work with power markets. Attend industry conferences or webinars to make connections and gain insights that could give you an edge in your application.
✨Tip Number 3
Showcase your experience with production-level programming by working on personal projects or contributing to open-source projects. This practical experience can demonstrate your ability to build robust systems, which is crucial for this role.
✨Tip Number 4
Prepare to discuss real-world scenarios where your forecasting models have impacted trading decisions. Being able to articulate your past experiences and their outcomes will highlight your commercial awareness and understanding of the business impact.
We think you need these skills to ace Data Scientist - Commodities
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in energy forecasting and algorithmic trading. Emphasise your skills in mathematical optimisation, machine learning, and programming languages like Python, Java, or C#.
Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about the role and how your background aligns with the company's needs. Mention specific projects where you've built forecasting models or worked with power markets.
Showcase Relevant Experience: When detailing your work history, focus on your achievements in developing production-level systems and your understanding of trading strategies. Use metrics to demonstrate the impact of your work on P&L and trading performance.
Highlight Technical Skills: Clearly list your technical skills related to system architecture, platform development, and real-time data processing. Mention any experience with stochastic programming, optimisation solvers, and time series forecasting techniques.
How to prepare for a job interview at Statera Talent
✨Showcase Your Technical Skills
Be prepared to discuss your experience with programming languages like Python, Java, or C#. Highlight specific projects where you've built production-level forecasting models, especially in power markets.
✨Demonstrate Market Knowledge
Familiarise yourself with the fundamentals of power markets and trading strategies. Be ready to discuss how your understanding of these concepts has influenced your previous work and decision-making.
✨Emphasise Problem-Solving Abilities
Prepare examples of how you've tackled complex problems using mathematical optimisation and machine learning techniques. Discuss the impact of your solutions on trading performance and P&L.
✨Communicate Effectively
Since stakeholder management is crucial, practice explaining your technical work in simple terms. Show that you can bridge the gap between data science and business needs, making it clear how your contributions drive value.
