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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 team 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 and exposure to cutting-edge technology.
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 (London Area) employer: Statera Talent
Contact Detail:
Statera Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Commodities (London Area)
✨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 how your skills can contribute to our real-time trading decisions.
✨Tip Number 2
Network with professionals in the commodities trading sector, especially those who work with power markets. Attend industry events or webinars to make connections and gain insights that could give you an edge during interviews.
✨Tip Number 3
Prepare to discuss specific projects where you've built production-level forecasting models. Be ready to explain the challenges you faced, the solutions you implemented, and the impact your work had on trading performance.
✨Tip Number 4
Showcase your understanding of the commercial aspects of trading. Be prepared to discuss how your technical skills in machine learning and optimisation can directly influence P&L and trading strategies in a high-stakes environment.
We think you need these skills to ace Data Scientist - Commodities (London Area)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in energy forecasting and algorithmic trading. Emphasise your strong mathematical optimisation and machine learning skills, as well as any relevant programming languages like Python, Java, or C#.
Craft a Compelling Cover Letter: In your cover letter, explain why you are passionate about the commodities market and how your background aligns with the role. Mention specific projects where you've built forecasting models or worked on production systems that had a direct impact on trading decisions.
Showcase Relevant Experience: When detailing your work experience, focus on roles where you developed real-time trading systems or worked with power market fundamentals. Use quantifiable achievements to demonstrate your impact on P&L and trading performance.
Highlight Technical Skills: Clearly list your technical skills related to system architecture, platform development, and any experience with stochastic programming or time series forecasting. This will show that you have the necessary expertise for the high-stakes environment of this role.
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.
✨Discuss Real-Time Systems Experience
Since this role involves building live systems, share examples of your experience with real-time data processing and automated model updates. Emphasise any challenges you faced and how you overcame them.
✨Highlight Stakeholder Management Skills
This position requires commercial awareness and stakeholder management. Prepare to discuss how you've effectively communicated complex technical concepts to non-technical stakeholders in past roles.
