Octopus EnergyWomen in Trading - Data Scientist
Octopus Energy is hiring a Women in Trading - Data Scientist. Level rates it ; you can apply on Level.
AI in this role
Build data pipelines and ML models for energy trading and forecasting at Octopus Energy Trading.
Supporting women in Trading in the energy industry:
At Octopus Energy, we’re on a mission to make energy fair, clean, and simple for all using technology. To get there, we need brilliant people with different backgrounds, experiences and perspectives helping us change the industry.
Women make up around 49% of the overall UK workforce, yet they occupy only about 20% of UK data science roles and under 20% of positions on trading desks. In senior quantitative and leadership roles, that representation shrinks further. We want to help change those numbers by creating a collaborative and supportive environment at Octopus Energy Trading, one where women in data science can build confidence, sharpen their technical craft, and step into lead roles.
We are actively encouraging applications from women to join our team across technical and trading roles. Forget traditional Trading floors! We have a unique culture within Trading; one of collaboration and genuine care about our colleagues.
You don't need extensive experience working in Trading or Energy. We’ll give you the training, support and tools you need to thrive. Previous Data Science experience is needed, but we’d also love to hear from people with a broad set of skills.
About Octopus Energy Trading:
At Octopus Energy Trading, we’re on a mission to reshape the future of energy. As part of Octopus Energy Group, we’re creating an innovative approach to trading that will accelerate the transition to a Net Zero world. With the growth of renewables and a push toward decarbonising heating and transport, greater flexibility in the grid is essential. We are building cutting-edge technology to optimise everything from domestic EV charging to grid-scale batteries, to meet the global demand for energy flexibility.
We’re looking for collaborative creators and curious problem-solvers to join us on this journey, bringing a diversity of experience and ideas to shape a more efficient, flexible, and sustainable energy system.
With an increase in variable and distributed supply, using data for trading and forecasting has never been more important. Octopus has always had a tech-first approach, and our trading and analytics tools are all built in-house. We are looking for a data scientist who’s comfortable building data pipelines bringing together internal and external data to create market leading insights using both classical and ML techniques. This will include looking at demand, renewables and transmission system fundamentals forecasts focussed to begin with on the GB intraday power market.
How we rate this
Women in Trading - Data Scientist at Octopus Energy rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where data science was part of your work. What did you do?
- Tell me about a project where forecasting was part of your work. What did you do?
- Tell me about a project where data pipelines was part of your work. What did you do?
- What's a project where you used Python hands-on?
- Walk me through how you've used Machine learning in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Data Science, Forecasting, Data Pipelines, Python, and Machine learning. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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