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Salary: GBP 75,000 - 200,000 / annual
Axle Energy is building software infrastructure for the decarbonised energy system. The company controls hundreds of thousands of energy assets—vehicle charging systems, heating systems, and home batteries—optimizing when energy is used to align with cheap and green electricity availability. Backed by Energize Capital and Accel, Axle operates at high speed in a legacy industry, moving real gigawatt-hours of electrons while scaling rapidly.
In this full-stack data science role, you will own the complete lifecycle of data science projects from exploration and prototyping through production deployment. Key responsibilities include:
- Building, optimizing, and deploying machine learning models that operate reliably at scale in production environments
- Developing deep domain expertise in electricity markets, grid dynamics, and trading strategies
- Writing clean, production-quality Python code and contributing to robust, scalable systems
- Moving beyond notebooks to deliver real-world, productionized solutions
- Collaborating across a small, flat-structured team and occasionally engaging directly with clients
The tech stack centers on Python for backend work, React for frontend (less relevant for this role), Docker for deployment, and Google Cloud Platform (GCP) for infrastructure. The company actively encourages exploration of AI tools like Claude Code to rethink workflows.
Axle operates with a deliberately flat structure and equitable pay philosophy (1:1 median ratio between founder and team compensation). The London office near Farringdon is dog-friendly, and the role is hybrid with an expectation of 2–3 days per week in-office to maximize collaboration. Additional benefits include meaningful equity, enhanced parental leave, and bi-annual team retreats.
**Requirements:**
- Strong data science fundamentals with ability to build and deploy models at scale
- Proficiency in Python and production-quality code practices
- Experience with time-series data analysis
- Knowledge of electricity systems and power trading (highly valued but not strictly required)
- Comfort engaging with clients and stakeholders
- Willingness to work across the full data science lifecycle, not just research/prototyping
