At a Glance
- Tasks: Lead data management for trading, ensuring accuracy and reliability of critical datasets.
- Company: Join an AI-first energy company revolutionising the energy sector with innovative technology.
- Benefits: Competitive salary, equity options, biannual bonuses, and fully expensed tech.
- Other info: Dynamic role with opportunities for global collaboration and career growth.
- Why this job: Make a real impact in the energy industry while working with cutting-edge data solutions.
- Qualifications: Proven experience in data product ownership and team leadership.
The predicted salary is between 90000 - 110000 £ per year.
Description Fuse is an AI-first energy company on a mission to make energy abundant and affordable, fast.
We combine first-principles thinking with cutting-edge technology to build a radically better energy system.
We've raised over $200M from top-tier investors including Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, 20VC, Hummingbird and Collaborative Fund, alongside strategic angels including Nico Rosberg and GPs behind Meta, Revolut, Spotify and Uber.
We're building a fully integrated energy company: developing our own solar, batteries and other generation projects, building our own hardware, improving and developing grid infrastructure, trading power in real time, and installing distributed energy in homes.
We're hiring a Data Lead to own trading data end to end, from the moment external data enters Fuse to the moment a trader or model relies on it.
You'll be accountable for whether that data is correct, timely, reproducible and actually useful, and you'll get it into production fast.
Responsibilities Own trading data as a product, covering power market data, weather forecasts, grid and system data, fuel prices and fundamentals, and be accountable for its reliability and usefulness to traders and quants.
Ship datasets and pipelines to production quickly and find and fix performance bottlenecks across ingestion, storage and delivery.
Evaluate, onboard and manage data vendors, including coverage, latency, licensing and cost against trading value.
Build and run monitoring for freshness, completeness and anomalies with a clear process when a feed breaks.
Lead and grow a team of engineers and map how data flows across the business so you can plug in new sources quickly and block decisions that would cause problems downstream.
Requirements Track record of owning and shipping data products to real users or customers, including the pipelines, data quality and delivery, and being accountable for outcomes rather than only the implementation.
Track record of leading people and coordinating across teams with a clear understanding of how data flows through a business.
Technical rigour: you can go deep, profile a system and untangle performance bottlenecks.
Strong schema design for time series and event data, including revisions, late-arriving data and entity mapping across vendors.
Strong Python and SQL and experience running production pipelines at scale.
Experience evaluating and negotiating with data vendors with a view on cost versus value.
Nice to have Built or ran a data vendor business or owned a comparable data product end to end.
Benefits Competitive salary and eligibility for equity Biannual bonus scheme Fully expensed tech to match your needs Private health insurance Breakfast and dinner allowance for office-based employees As we hire globally, benefits may vary by location.
Job Summary ID: 3B5F181FF9Department: Type: full time
Data & AI Lead in London employer: Fuse Energy Supply
Fuse Energy is an exceptional employer, offering a dynamic work environment where innovation meets purpose in the renewable energy sector. With a strong focus on employee growth, we provide opportunities for continuous learning and development, alongside competitive salaries and equity bonuses. Our collaborative culture encourages knowledge sharing and empowers team members to take ownership of their projects, making it a rewarding place for Software Engineers looking to make a meaningful impact.
StudySmarter Expert Advice🤫
We think this is how you could land Data & AI Lead in London
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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 Data & AI Lead 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!
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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!
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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
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✨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.
