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About the Role

The purpose of this position is to improve the scope of energy market forecasts and ultimately the profitability of trades by developing advanced time-series forecasting models, initially focusing on meteo-to-power predictions and expanding to other time-series.

Responsibilities

• Develop and refine time-series forecasting models, including meteo-to-power (wind and solar).
• Continuously add features to models as renewable energy integration increases.
• Expand forecasting capabilities to other time-series.
• Ensure forecast accuracy and timely delivery to traders.
• Assist with daily team operations, including data collection and market intelligence.
• Liaise with Data teams to set up new data feeds and monitor existing ones.
• Run and automate forecast models.
• Maintain dashboards and reports.
• Provide proactive modeling advice to analysts and stakeholders.
• Develop an in-depth understanding of power fundamentals.

Requirements

• Some experience in the energy market or a trading environment is beneficial but not essential.
• Proven academic excellence in the field.
• A couple of years of experience building production-grade models (MLOps) is essential.
• Strong Python coding experience/knowledge is essential.
• Knowledge of Git and CI/CD practices.
• Demonstrable proficiency with packages such as Pandas, Sklearn, Pytorch, or Keras.
• Knowledge of SQL and Excel.
• Experience with Databricks is welcome.
• Excellent analytical skills and attention to detail.
• Ability to work effectively in a fast-paced environment with evolving market and business needs.
• Strong team player with good communication skills, comfortable discussing technical details with senior stakeholders.
• Willingness to learn and incorporate technical features of power fundamentals.

Skills

• Time-series forecasting
• Machine Learning
• Data Science
• Statistics
• Python
• Pandas
• Sklearn
• Pytorch
• Keras
• Git
• CI/CD
• SQL
• Excel
• Databricks
• Analytical skills
• Communication

Location

• London
• Paris
• Singapore
• Houston

Work Type

• Hybrid working

Experience Level

• A couple years experience with building production-grade models

Education Level

• Advanced graduate qualification (PhD or postdoctorate) in Machine Learning, Data Science, Statistics or Maths

Benefits

• Hybrid working (location dependent)
• Personal pension plan
• Private medical and dental insurance
• Bi-annual health assessments
• Corporate gym memberships
• Electric car lease programme
• Childcare vouchers
• Cycle-to-work scheme
• Season ticket loans
• Volunteering opportunities

About the Company

• EDF Trading is part of the EDF Group, a world leader in low-carbon, sustainable electricity generation.
• We are a diverse international team of experts in energy markets.
• We trade in power, gas, LNG, LPG, oil, and environmental products.
• We have over 20 years of experience and are leaders in the field.
• We manage assets for EDF Group and customers globally, ensuring efficiency and expert risk management.
• Our culture values self-discipline, hard work, inquisitiveness, trustworthiness, and truthfulness.
• We prioritize team success and making a difference.
• We are committed to employee development with a wide range of technical and personal courses.
• We are proud of our work ethic and cultural diversity.
• We are high-performing people working together to achieve common goals.
• We are innovative and flexible in our thinking, adapting to change for success.
• Issues are met with feedback, solutions, and discussion; mistakes are seen as experiences, not failures.

Equal Opportunity

• Gender balance and inclusion are very high on the agenda at EDF Trading.