Allye

Data Scientist - Battery Energy Storage

UK
Python AWS GCP Machine Learning
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Description

Company Description

We are an ally for the grid, the people and the planet. Our battery energy storage makes energy more affordable, cleaner and accessible for everyone so that every factory, business and home to reduce their energy bills by up to 50% while providing flexibility to the grid to lower costs and accelerate decarbonisation.

Our first system, the Allye Max, is an innovative 320kWh mobile energy storage system using repurposed electric vehicle batteries. It is two-times cheaper and has 60% lower embedded CO2 than other similar systems. Our teams are developing the hardware and software solutions to transform our energy is managed at the grid-edge.

Job Description

We are seeking a passionate Data Scientist with a specialisation in real-time trading of electricity markets, AI and machine learning with energy storage

This role represents a unique opportunity to work within a rapidly growing and dynamic company. In this role, you will apply quantitative analysis and data science techniques to develop sophisticated models for energy trading, risk assessment, and market analysis. Your work will directly contribute to the strategic positioning of our energy storage assets in the market, optimizing their financial performance.

This is an exciting role that offers the opportunity to be at the forefront of an emerging industry and make a lasting impact on the future of energy storage.

The ideal candidate will have a background in engineering or computer science either in energy storage, electric vehicles or financial markets and a strong understanding of the energy transition.
 

Responsibilities

  • Develop and maintain advanced models for real-time trading and arbitrage across multiple power grid ancillary services.
  • Perform statistical analysis and back-testing to refine trading strategies and assess their performance.
  • Develop predictive models for market prices, demand, and supply dynamics using machine learning techniques.
  • Design and implement algorithms for automated trading and real-time decision-making
  • Monitor and respond to market conditions in real-time, adjusting strategies as necessary to maximize returns.
  • Communicate complex quantitative analysis and model results to stakeholders in a clear and concise manner.

Qualifications

Must-haves

  • Advanced Degree (PhD preferred) in Computer Science, Data Science, Financial Engineering, or a related field.
  • Proven experience in real-time trading and arbitrage modelling, preferably within the energy sector.
  • Strong proficiency in Python, and experience with other programming languages and statistical tools.
  • Deep understanding of ancillary services markets and energy trading principles.
  • Experience with high-frequency data analysis and algorithmic trading systems.
  • Experience with time-series analysis and forecasting methods.
  • Must be self-motivated and an effective team player.
  • Eligible to work in the UK.

Nice-to-haves

  • An interest in the energy sector and sustainable technologies.
  • Experience with real-time trading platforms and algorithmic trading.
  • Experience with cloud computing platforms, such as AWS or GCP, for deploying trading models.
  • Experience with advanced machine learning techniques, including reinforcement learning and neural networks.

Additional Information

We believe that diversity drives innovation. Be a part of our journey to revolutionise the energy storage industry by introducing more sustainable and superior products to the market.

Applications

Please note that at this time we are unable to provide UK visa sponsorship

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