Data Engineer
London, United Kingdom
EDF Trading
Come work at a place where innovation and teamwork come together to support the most exciting missions in the world!
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.
Most of all, we value our people. Become part of the team and you will be offered a great range of benefits which include hybrid working, a personal pension plan, private medical and dental insurance, bi-annual health assessment, corporate gym memberships, electric car lease programme, childcare vouchers, cycle to work scheme, season ticket loans, volunteering opportunities and much more. We even provide free fruit to keep you healthy.
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 800 colleagues based in London, Paris, Singapore, Tokyo 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 partnered with JERA, one of Japan’s largest utilities; the perfect organisation at which to begin or progress your career in the commodities sector.
Join us, make a difference and help shape the future of energy.
Job Description:
Team / department
Energy Analytics - This is a Front Office role on the Gas Trading Desk, working directly with traders and analysts
Position purpose
Development and maintenance of the Gas Analytics forecasting models and data systems
Main responsibilities
- Development and maintenance of the forecasting models and data systems
- Coming up with creative ways to accurately forecast phenomena of interest
- Continuously monitor and adjust models to maximize predictive power
- Development of desk Python libraries
- Work together with analysts and traders to understand stakeholders' needs when designing solutions
- Analyse data to support quantitative decision-making
- Development and maintenance of webpages summarizing analytics for effective decision-making
- Apply CI/CD best practices and ensure DevOps style management and operation of DEV/UAT/PROD deployment environments
Required Skills and Experience (1-3 years)
- Experience working on shared codebase, debugging and improving existing code
- Experience in building and maintaining forecasting models, managing entire model lifecycle
- Experience in the sourcing, cleaning and storing of data from multiple sources
- Experience with data analysis and visualisation
- Ability to work independently and switch between different contexts/tasks
- Some experience of working in the energy market or prior exposure to a trading environment would be beneficial
Technical Requirements
- STEM degree
- Excellent Python skills
- Statistics knowledge
- SQL and basic understanding of databases
- Basic Git knowledge for collaborative coding
Person Specification
- Interest in becoming autonomous quickly
- Rigorous and structured approach
- Detail-oriented and quality-conscious
- Possess a collaborative mindset
- Ability of working in a fast-paced environment
- Strong communication skills
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile CI/CD Data analysis DevOps Git Python SQL Statistics STEM
Perks/benefits: Career development Flex hours Health care Team events
More jobs like this
Explore more career opportunities
Find even more open roles below ordered by popularity of job title or skills/products/technologies used.