At a Glance
- Tasks: Develop and implement quantitative models for renewable energy trading and risk management.
- Company: Join a forward-thinking startup on a mission to revolutionise renewable energy.
- Benefits: Competitive salary, equity bonus, tech allowance, and paid leave.
- Other info: Dynamic team environment with opportunities for growth and innovation.
- Why this job: Make a real impact in the renewable energy sector with cutting-edge technology.
- Qualifications: 1+ years in quantitative modeling, strong Python skills, and data analysis experience.
The predicted salary is between 60750 - 74250 £ per year.
Fuse Energy is a forward-thinking renewable energy startup on a mission to deliver a terawatt of renewable energy - fast. We're combining first-principles thinking with cutting-edge technology to build a radically better energy system.
We’re creating a fully integrated energy company: from developing solar, wind and hydrogen projects to real-time power trading and distributed energy installations. By selling directly to consumers, we cut out the middleman, lower costs and pass on savings to customers.
But we’re not stopping there. We’re also building the Energy Network: a decentralised platform of smart devices to electrify our homes, shifting usage to off-peak hours and helping balance the grid. This network strengthens grid stability - a critical foundation for scaling AI data centers and other energy-intensive industries.
Responsibilities
- Develop and implement quantitative models to support hedging strategies for retail energy supply
- Analyze market data to optimize the performance of physical assets such as solar and wind farms
- Conduct statistical and scenario-based modeling to inform trading and risk management decisions
- Monitor power markets, pricing trends, and regulatory developments to identify risks and opportunities
- Collaborate with engineering and operations teams to integrate models into day-to-day decision-making
Requirements
- 1+ years of experience in quantitative modeling, data analysis, or a related role in energy, trading, or analytics
- Strong proficiency in Python, with experience using libraries for data analysis, modeling, and visualization
- Solid understanding of statistical modeling, optimization, and analysis techniques
- Experience working with time series or market data, preferably in energy or commodities markets
- Strong problem-solving skills and the ability to translate complex data into actionable insights
Benefits
- Competitive salary and an equity sign-on bonus
- Biannual bonus scheme
- Fully expensed tech to match your needs
- Paid annual leave
- Breakfast and dinner allowance for office based employees
Quantitative Researcher in London employer: Fuse Energy Supply
Fuse Energy is an exceptional employer for Senior Mobile Engineers, offering a dynamic and innovative work environment in the heart of London. With a strong focus on employee ownership and autonomy, you'll have the opportunity to shape products from concept to launch while working alongside a talented team dedicated to revolutionising the renewable energy sector. The company provides competitive salaries, equity bonuses, and a culture that prioritises personal growth and cutting-edge technology, making it an ideal place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Researcher in London
✨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 Fuse Energy Supply!
✨Show Off Your Projects
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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 Fuse Energy Supply.
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We think you need these skills to ace Quantitative Researcher in London
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 Fuse Energy Supply, 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 Fuse Energy Supply. 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 Fuse Energy Supply
✨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 Fuse Energy Supply!
✨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.
