At a Glance
- Tasks: Lead the development of advanced forecasting models for European power markets.
- Company: Fast-growing energy trading and optimisation business with a focus on innovation.
- Benefits: Competitive salary, remote work options, and clear career progression.
- Other info: Join a dynamic team at an exciting stage of expansion.
- Why this job: Shape the future of energy forecasting and influence live trading decisions.
- Qualifications: 2-3+ years in energy trading, strong Python skills, and quantitative modelling experience.
The predicted salary is between 63000 - 77000 £ per year.
- Senior Quantitative Analyst / Lead Data Scientist – Energy – UK (Remote) – £70 - 80k
- Job Type: Permanent, Full Time
The Opportunity
EVEREC is partnering with a fast-growing energy trading and optimisation business to recruit a Senior Quantitative Analyst / Lead Data Scientist to lead the development of next-generation forecasting models across European power markets.
This is a unique opportunity to work directly alongside the Head of Optimisation Strategy, developing forecasting capabilities that feed straight into live trading decisions.
As one of the first hires in this function, you'll play a key role in shaping the company's forecasting strategy, with a clear pathway to Head of Forecasting as the team expands.
Working across Battery Energy Storage Systems (BESS), solar, wind and co-located renewable assets, you'll develop cutting-edge forecasting models that directly influence trading performance and commercial outcomes.
Key Responsibilities
- Design, develop and deploy advanced forecasting models for European electricity markets.
- Build time series and machine learning models to forecast power prices, renewable generation, imbalance prices and market signals.
- Analyse market data from exchanges including EPEX Spot, Nord Pool and other European energy markets.
- Work closely with traders to translate forecasting outputs directly into trading strategies.
- Translate forecasting outputs into actionable inputs for the optimisation team, supporting BESS, solar PV, wind and co-located renewable asset decisions.
- Monitor, improve and maintain forecasting model performance from research through to production.
- Identify new data sources and modelling approaches to improve forecast accuracy and commercial performance.
- Collaborate with engineering and software teams to deploy scalable forecasting solutions.
About You
We're looking for an experienced quantitative professional with deep forecasting expertise and a genuine understanding of how European energy markets function.
You will ideally have
- 2-3+ years' experience within an energy or commodity trading environment, with direct exposure to how power markets actually operate.
- Strong background in quantitative modelling, statistics and time series forecasting.
- A proven track record building and deploying forecasting models yourself — hands-on in Python, from research through to production.
- Experience developing machine learning or deep learning forecasting models.
- Experience working with electricity market data such as EPEX Spot, Nord Pool or other European exchanges.
- Understanding of how BESS, solar, wind and co-located assets generate value in power markets, and how forecasts feed trading and dispatch decisions.
- Strong programming skills using Python and relevant data science libraries.
- Excellent analytical and problem-solving skills.
- Ability to work closely with traders and commercial teams in a fast-paced environment.
- What's On Offer
- Salary of £70,000 to £80,000 depending on experience.
- Remote working within the UK or hybrid working in Stockholm.
- Opportunity to build and lead the forecasting function.
- Clear progression to Head of Forecasting.
- Exposure to live trading strategies and real-time market decision-making.
- Work on cutting-edge BESS and renewable energy projects across European power markets.
- Join a fast-growing business at an exciting stage of expansion.
If you're an experienced Quantitative Analyst or Data Scientist with deep forecasting expertise, looking to shape the future of forecasting within one of Europe's fastest-growing energy trading businesses, we'd love to hear from you.
Apply via Linked In or email your CV to
Senior Quantitative Analyst / Lead Data Scientist – Energy – London (Remote) – £70 - 80k in Manchester employer: EVEREC
Join a forward-thinking company in Whitstable, Kent, where as a Senior Electrical Project Manager, you'll play a pivotal role in shaping the future of EV charging infrastructure. With a strong emphasis on employee growth and collaboration, you will benefit from a supportive work culture, competitive salary, and an electric company car, all while contributing to a long-term contract that offers job security and the opportunity to lead a new division within a dynamic team.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Quantitative Analyst / Lead Data Scientist – Energy – London (Remote) – £70 - 80k in Manchester
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like EVEREC!
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Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Quantitative Analyst / Lead Data Scientist – Energy – London (Remote) – £70 - 80k at EVEREC.
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like EVEREC.
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We think you need these skills to ace Senior Quantitative Analyst / Lead Data Scientist – Energy – London (Remote) – £70 - 80k in Manchester
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at EVEREC, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at EVEREC. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at EVEREC
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at EVEREC!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
