At a Glance
- Tasks: Develop forecasting and optimisation models for a peer-to-peer renewable energy trading platform.
- Company: Join a rapidly scaling company transforming the energy market with innovative technology.
- Benefits: Enjoy a competitive salary, hybrid work, and opportunities for professional growth.
- Why this job: Make a real impact in the renewable energy sector while working with cutting-edge data science.
- Qualifications: Proficiency in Python, time-series modelling, and experience with cloud environments required.
- Other info: Collaborate in a dynamic startup environment with excellent career advancement potential.
The predicted salary is between 36000 - 60000 £ per year.
Location: London (Hybrid)
Employment Type: Full‑time, Permanent
About The Company
We are a rapidly scaling peer‑to‑peer Power Purchase Agreement (PPA) platform enabling businesses, generators, and communities to buy and sell renewable electricity directly. Our purpose is to accelerate the shift to a decentralised, transparent, and data‑driven energy system. We build intelligent systems that optimise matching, pricing, and forecasting across distributed generation and consumption. As we expand across the UK and Europe, we are adding strong analytical and modelling capability to our team.
Role Overview
We are hiring a Data Scientist to develop the forecasting, optimisation, and analytical models that underpin our trading platform. You will design, build, and deploy production‑grade models using energy‑market data, asset telemetry, weather data, settlement data, and commercial datasets. This role is central to the evolution of our pricing, risk, trading, and optimisation engines. You will collaborate closely with engineering, product, and commercial teams and work with a high degree of autonomy.
Responsibilities
- Modelling and Forecasting
- Build time‑series models for generation, consumption, and market price forecasting.
- Develop probabilistic and scenario‑based forecasting capabilities.
- Apply machine learning to optimise matching, pairing, and routing algorithms within the P2P marketplace.
- Trading and Optimisation Intelligence
- Create algorithms that optimise buyer–seller matching, pricing, and load balancing.
- Support automated PPA structuring, risk scoring, and exposure modelling.
- Develop data‑driven insights to improve trading efficiency and platform performance.
- Data Infrastructure and Engineering
- Work with engineers to design and maintain pipelines for market data, weather feeds, asset data, and settlement information.
- Implement scalable analytics environments and deploy models into production.
- Product and Cross‑Functional Collaboration
- Translate modelling outputs into dashboards, APIs, scoring engines, and product features.
- Provide input into product strategy based on model performance and market trends.
- Communicate insights clearly to non‑technical stakeholders.
- Market and Commercial Analytics
- Analyse energy market signals, PPA structures, pricing models, and regulatory factors.
- Develop intelligence around imbalance exposure, generation patterns, demand profiles, and commercial optimisation.
Qualifications
Required Skills And Experience
- Technical Skills
- Proficiency in Python and associated data science libraries (NumPy, Pandas, SciPy, scikit‑learn, PyTorch/TensorFlow).
- Strong experience with time‑series modelling (ARIMA, Prophet, LSTMs or similar).
- Understanding of optimisation methods (linear, mixed‑integer, reinforcement learning desirable).
- Strong SQL and practical experience with production‑ready data pipelines.
- Experience working with cloud environments (AWS, GCP, or Azure).
- Energy and Market Experience (Highly Desirable)
- Understanding of electricity markets, PPAs, forecasting, imbalance settlement, or asset telemetry.
- Experience with data sources such as system operator data, market pricing feeds, or weather‑driven asset forecasting.
- Professional Skills
- Ability to work in a fast‑paced startup environment with autonomy and ambiguity.
- Strong communication and problem‑solving skills.
- Ability to convert complex analytical outputs into actionable business recommendations.
- Nice to Have
- Experience with marketplace or matching algorithms.
- Exposure to flexibility markets, virtual power plants, or reconciliation/settlement processes.
- Experience with ML deployment frameworks (MLflow, Vertex AI, SageMaker).
- Knowledge of optimisation libraries such as Gurobi, OR‑Tools, or Pyomo.
Data Scientist – Peer‑to‑Peer Renewable Energy Trading Platform - The Green Recruitment Company employer: Jobster
Contact Detail:
Jobster Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist – Peer‑to‑Peer Renewable Energy Trading Platform - The Green Recruitment Company
✨Tip Number 1
Network like a pro! Reach out to people in the renewable energy sector, especially those working in data science. Attend industry events or webinars, and don’t be shy about sliding into DMs on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those related to energy markets or predictive modelling. This will not only demonstrate your expertise but also give you something tangible to discuss during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and SQL skills. Practice common data science problems and be ready to explain your thought process. Remember, they want to see how you approach problem-solving, so think aloud!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team. Don’t forget to tailor your application to highlight your experience with time-series modelling and optimisation methods!
We think you need these skills to ace Data Scientist – Peer‑to‑Peer Renewable Energy Trading Platform - The Green Recruitment Company
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with Python, time-series modelling, and any relevant projects that showcase your skills in forecasting and optimisation. We want to see how you can contribute to our peer-to-peer renewable energy trading platform!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about renewable energy and how your background aligns with our mission. Don’t forget to mention specific experiences that relate to the responsibilities outlined in the job description.
Showcase Your Technical Skills: We’re looking for someone with strong technical skills, so make sure to highlight your proficiency in Python and any data science libraries you've used. If you have experience with cloud environments or machine learning frameworks, be sure to include that too!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Jobster
✨Know Your Data Science Stuff
Make sure you brush up on your Python skills and the data science libraries mentioned in the job description. Be ready to discuss your experience with time-series modelling and optimisation methods, as these are crucial for the role.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex problems in previous roles. Think about how you can translate analytical outputs into actionable business recommendations, as this will be key in demonstrating your value.
✨Understand the Energy Market
Familiarise yourself with electricity markets, PPAs, and the factors that influence pricing models. Being able to discuss these topics will show your genuine interest in the industry and help you stand out from other candidates.
✨Communicate Clearly
Practice explaining technical concepts in simple terms, especially since you'll need to communicate insights to non-technical stakeholders. Clear communication is essential in a collaborative environment, so make sure you're prepared to demonstrate this skill.
