Analysis Intern

When you join EDF Trading, you’ll become part of a diverse international team of experts who challenge conventional ideas, test new approaches, and think outside the box.

Energy markets evolve rapidly, so our team needs to remain agile, flexible, and ready to spot opportunities across all the markets we trade in power, gas, LNG, LPG, oil, and environmental products.

EDF Group and our customers all over the world trust that their assets are managed by us in the most effective and efficient manner and are protected through expert risk management. Trading for over 20 years, it’s experience that makes us leaders in the field. Energy is what we do.

Become part of the team and you will be offered a great range of benefits, which include (location dependent) hybrid working, a personal pension plan, private medical and dental insurance, bi-annual health assessments, corporate gym memberships, an electric car lease programme, childcare vouchers, a cycle-to-work scheme, season ticket loans, volunteering opportunities, and much more.

Gender balance and inclusion are very high on the agenda at EDF Trading, so you will become part of an ever-diversifying family of around 750 colleagues based in London, Paris, Singapore, and Houston. Regular social and networking events, both physical and virtual, will ensure that you always feel connected to your colleagues and the business.

Who are we? We are EDF Trading, part of the EDF Group - a world leader in low-carbon, sustainable electricity generation.

Join us, make a difference, and help shape the future of energy.

Job Description:

Department

The Short-Term Analytical Team is an operational team with the following structure:

6 market analysts and a manager supporting the Short term Power Desk during week days :

• 3 analysts are working on Intraday horizon in Paris
• 3 analysts are working on Day Ahead and Week Ahead horizons in London
• The analysts on shift models the whole European electricity system in order to support the desks for the price forecast and trading strategy

7 analysts and a manager dedicated to the optimization of the EDF portfolio on Day Ahead and Week Ahead horizon.

• These analysts are working 7/7 in Paris.
• The analyst on shift models the available flexibility of the EDF system and translates it into EPEX orders to realise an economically efficient optimisation on the Day Ahead electricity market
• These epex orders are also forecasted up to 21 days in advance for the Week-Ahead hedging purposes

The Analytics Engineering Manager and 2 software engineers

Position purpose

Price forecasting models are central in EDF Trading activities, especially for optimisation and bidding construction purposes. One of the key elements is to forecast up to 21 days in advance the market orders of the EDF plants portfolio the most accurately possible.

The main agenda of the internship is to be able to refine these forecasts either with statistical method (statistical inference, machine learning model…) or with optimisation tools used in elaborate fashion with relevant tweaks.

The first focus is the assessment of the gap between forecasted market orders and actuals. Clear and accurate visualization of these variances is essential for all key stakeholders, including analysts, traders, and optimization teams.
The second focus is refining identified discrepancies, followed by the implementation of corrective actions within the production environment.

The outcome will be evaluated by backtesting the new methodology with real market and optimisation data.

Main responsibilities

• Design and propose a dashboard to assess the gap between forecasted and actual market orders.
• Propose and implement methodologies aimed at reducing or mitigating this gap.
• Ensure robust, well-documented implementation of models prior to deployment in the production environment.
• Analyse outcomes and communicate findings to the team, Traders, and Optimizers.

Person specifications & Technical requirements

Must demonstrate strength in:

• Interest in energy markets
• Quantitative and statistical modelling
• Optimisation modelling
• Python
• Good communication skills
• Strong collaborator

Duration: 6 months

Hours of work:

35 hours per week, Monday to Friday