At a Glance
- Tasks: Develop and enhance forecasting models for energy markets using machine learning.
- Company: Join a leading energy trading organisation with a focus on analytics.
- Benefits: Gain exposure to real-world applications and collaborate with industry experts.
- Other info: Dynamic role with opportunities for career growth in energy trading analytics.
- Why this job: Make a direct impact on trading decisions in a fast-paced environment.
- Qualifications: PhD in a quantitative field and experience in data science or machine learning.
The predicted salary is between 40000 - 50000 £ per year.
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.
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
- A Ph D 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, Num Py 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.
- Exposure to energy markets, commodities or financial markets.
- Experience with time-series forecasting techniques.
- Knowledge of cloud platforms or distributed computing.
- Familiarity with Tensor Flow, Py Torch or similar machine learning frameworks.
- Experience using Git and software development best practices.
- #J-18808-Ljbffr
Data Scientist - Energy Trading in London employer: Bonhill Partners
Bonhill Partners offers an exceptional work environment for Data Engineers, providing the opportunity to engage with cutting-edge technologies in a dynamic global commodities trading setting. Employees benefit from a culture of innovation and collaboration, alongside ample opportunities for professional growth and development. Located in a vibrant industry hub, the company fosters a supportive atmosphere that values creativity and encourages team members to push the boundaries of data engineering.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist - Energy Trading 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 Bonhill Partners.
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We think you need these skills to ace Data Scientist - Energy Trading 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 Bonhill Partners, 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 Bonhill Partners. 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 Bonhill Partners
✨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 Bonhill Partners!
✨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.
