Data Scientist - Energy Market Analysis and Prediction
Join a CleanTech startup building software to shift energy usage, coordinating EV charging, home batteries, and heating systems. As a Data Scientist, you'll own end-to-end work, from hypothesis to production systems, and develop ML models predicting demand and automating decisions.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
๐ป Job Title: Data Scientist
๐ฐ Salary: ยฃ60-120k (+ generous early stage equity)
๐ Location: Central London, EC1 (2-3 office days/week)
๐ฆ Company: CleanTech / ClimateTech / EnergyTech
๐ฅ Employees: ~30
๐ธ Funding: $10m+ (Seed)
The planet has an energy problem. You can help fix it.
This London startup is building software that intelligently shifts when energy gets used - coordinating EV charging, home batteries and heating systems across hundred of thousands of assets in real time.
The result: cheaper bills, greener grids and a system that actually works for the future. Their ML models sit at the heart of it all, predicting demand and automating decisions at a scale that genuinely moves the needle on emissions.
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Backed by some of the best investors in the world, they have serious momentum behind them and are looking for multiple Data Scientists to join their mission.
About the role
This isn't a research job where your models live in notebooks forever. You'll own your work end-to-end - from the initial hypothesis through to production systems that run in the real world, at scale, every day.
You'll get deep into energy markets and grid dynamics, building the kind of domain expertise that's genuinely rare (and valuable! - should you ever choose to leave us). You'll write production-quality Python, collaborate closely with engineers, and push ideas from prototype to deployment without throwing things over a wall.
If you're the kind of person who gets a kick out of seeing something you built running in production - and finds energy markets genuinely fascinating - you'll fit right in.
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The stack
- Python
- Docker
- GCP
- Streamlit for internal tooling
- Figma for rapid prototyping before anything gets built
- No unnecessary complexity - just tools that help move fast and build things that last.
โ You'll thrive here if you:
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- Have strong ML fundamentals and know how to take models beyond the notebook
- Write clean, production-ready Python and care about code quality
- Are comfortable owning the full lifecycle of your work
- Are curious about how energy systems, grids, and markets actually function
- Can talk to non-technical stakeholders without breaking a sweat
๐ Bonus points for:
- Experience with time-series data
- Background in power trading or electricity markets
- Comfort working directly with clients
๐ VISA sponsorship is available if needed.
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