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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 impactful trading decisions.
- Benefits: Enjoy a high-stakes role with real-time decision-making and potential for significant impact.
- Why this job: Be part of a dynamic team where your work directly influences trading performance.
- Qualifications: Experience in energy forecasting, strong programming skills, and knowledge of power markets required.
- Other info: This is a front-office role with mission-critical responsibilities.
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.
Contact Detail:
Statera Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Commodities
✨Tip Number 1
Network with professionals in the commodities and energy trading sectors. Attend industry conferences, webinars, or local meetups to connect with potential colleagues and learn about the latest trends in power market modelling.
✨Tip Number 2
Showcase your practical experience by discussing any relevant projects you've worked on. Be prepared to explain how your forecasting models have impacted trading decisions or improved efficiency in previous roles.
✨Tip Number 3
Stay updated on the latest developments in machine learning and optimisation techniques. Familiarise yourself with tools and frameworks that are commonly used in the industry, as this will demonstrate your commitment to continuous learning.
✨Tip Number 4
Prepare for technical interviews by brushing up on your programming skills, particularly in Python, Java, or C#. Be ready to solve real-time data processing problems and discuss your approach to building robust trading systems.
We think you need these skills to ace Data Scientist - Commodities
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant 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 Technical Skills: Include specific examples of your technical skills in your application. Discuss any production-level systems you've developed and how they contributed to trading decisions or improved performance.
Highlight Commercial Awareness: Demonstrate your understanding of the commercial aspects of trading and how your work impacts P&L. Mention any experience you have with stakeholder management and how you've communicated complex data insights to non-technical audiences.
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 forecasting models or trading systems, and be ready to explain the technical challenges you faced and how you overcame them.
✨Demonstrate Market Knowledge
Familiarise yourself with current trends in power markets and trading strategies. Be ready to discuss how your understanding of market fundamentals can influence trading decisions and the importance of real-time data processing in your work.
✨Prepare for Problem-Solving Questions
Expect to tackle hypothetical scenarios related to market forecasting and optimisation. Practice explaining your thought process clearly and logically, as this will demonstrate your analytical skills and ability to make high-stakes decisions under pressure.
✨Emphasise Collaboration and Communication
Since this role involves stakeholder management, be prepared to discuss how you've worked with cross-functional teams in the past. Share examples of how you communicated complex technical concepts to non-technical stakeholders, ensuring everyone is aligned on project goals.
