Bonhill Partners
Data Scientist - Energy Trading

How your CV stacks up
Upload your CV to see how well it fits this job role
?%
We're partnering with a leading energy trading organisation to recruit a talented Data Scientist to join its growing Analytics team. This is an exciting opportunity for an early-career Data Scientist with a strong academic background and a passion for applying machine learning to real-world energy markets. Working alongside experienced Data Scientists, Quantitative Analysts and Traders, you'll help develop forecasting models that support trading decisions across power, gas and other energy markets.
If you're looking to combine advanced analytics with a fast-paced commercial environment, this role offers the chance to work on challenging problems with direct business impact.
The Role
As a Data Scientist, you'll contribute to the development and enhancement of forecasting models using machine learning and statistical techniques. You'll analyse complex datasets, identify market signals and help deliver predictive insights that support Front Office trading activity.
You'll work collaboratively across Trading, Quantitative Analytics and Technology teams, gaining exposure to both the technical and commercial aspects of energy trading.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Key Responsibilities
- Develop and improve forecasting models for energy markets, including power and gas.
- Apply machine learning and statistical techniques to predict prices, demand and other key market variables.
- Analyse large datasets from market, weather, generation and trading sources to identify predictive patterns.
- Support the design, testing and validation of forecasting models.
- Build and maintain data pipelines to support model development and deployment.
- Collaborate with Traders and Quantitative Analysts to understand business requirements and translate them into analytical solutions.
- Monitor model performance and recommend enhancements.
- Present findings and insights to both technical and non-technical stakeholders.
- Keep up to date with developments in machine learning and forecasting methodologies.
About You
We're looking for someone with a strong quantitative background who enjoys solving complex problems and wants to build a career in energy trading analytics.
You'll ideally have:


Get help with your application
Your very own career expert that helps elevate your application to the next level.
- A PhD in Mathematics, Statistics, Physics, Computer Science, Machine Learning, Data Science or another highly quantitative discipline.
- 1–3 years' commercial experience as a Data Scientist, Machine Learning Engineer or Quantitative Analyst.
- Experience developing forecasting or predictive models using machine learning techniques.
- Strong Python programming skills and experience with common data science libraries such as Pandas, NumPy and Scikit-learn.
- Experience working with SQL and large datasets.
- A solid understanding of statistics, time-series analysis and predictive modelling.
- Strong problem-solving and analytical skills.
- Excellent communication skills and the ability to explain technical concepts clearly.
Desirable Experience
- Exposure to energy markets, commodities or financial markets.
- Experience with time-series forecasting techniques.
- Knowledge of cloud platforms or distributed computing.
- Familiarity with TensorFlow, PyTorch or similar machine learning frameworks.
- Experience using Git and software development best practices.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location