Allye Energy is building an intelligent energy management platform that transforms how businesses and communities store, share, and optimise electricity. We're creating "energy banking" that combines battery storage with AI-powered software to make clean energy more accessible, affordable, and flexible.
By installing batteries at businesses and alongside legacy grid infrastructure, Allye Energy is building a network of distributed energy storage assets that solve local grid constraints, stabilise networks, and reduce energy costs. Our energy banking model makes energy storage 100 times more affordable for all consumers, providing the flexibility to deposit and withdraw electricity from shared batteries across our network. This revolutionary approach empowers local communities, creates a smarter grid, and accelerates the transition to renewable energy.
Job DescriptionAre you a Data Science, Statistics, or Computer Science student, recent graduate or apprentice who has practical hands-on experience with time series forecasting, optimization algorithms and statistical modeling? Do you love working with energy data, building predictive models and solving optimization problems in your spare time? Ideally you've participated in energy forecasting competitions, worked on projects related to demand prediction, battery optimization or linear programming; you want to demonstrate your analytical skills; and want to work in a fast-paced start up environment.
This is a unique opportunity to join a fast-growing London based start-up that is creating an all-new range of battery storage systems for both commercial and consumer markets. You will be responsible for developing forecasting models for energy demand, building optimization algorithms for battery charge/discharge cycles, and creating data pipelines to support our real-time energy management systems.
This internship will give you a unique opportunity to join us at the beginning of our journey, a business where you can contribute, grow and be a success.
QualificationsMust-haves
- Hands-on experience with time series analysis and forecasting (ARIMA, Prophet, LSTM)
- Strong programming skills in Python with experience in pandas, NumPy, scikit-learn
- Experience with optimization libraries (PuLP, OR-Tools, Gurobi) and linear programming
- Understanding of statistical concepts and model validation techniques
- Ability to work proactively with minimal support using a logical approach in an environment with minimal documented processes
- Must be self-motivated and an effective team player
- Eligible to work in the UK
Nice-to-haves
- Experience with energy market data and electricity price forecasting
- Knowledge of battery degradation modeling and charge optimization algorithms
- Experience with real-time data processing and streaming analytics
- Familiarity with cloud platforms (AWS/Azure) and MLOps practices
- Understanding of reinforcement learning for dynamic optimization
- Experience with IoT sensor data and anomaly detection
- Knowledge of power systems and grid operations
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.
Additional InformationPlease note that at this time we are unable to provide UK visa sponsorship
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