Data Science

Axle-Energy; Greater London; Hybrid; GBP 75,000 - 200,000; Full time

Benefits offered by this job

Equity stake

Competitive salary

Hybrid work model

Parental leave

Team retreats

Job summary

Axle Energy is hiring full stack data scientists who thrive on digging into the domain and delivering end-to-end data solutions. You will own models from exploration to production, with a strong emphasis on commercial value and energy market insight.

We operate with a flat structure and offer total compensation including equity, with a hybrid work model and a dog-friendly office near Farringdon.

Qualifications

• Experience as a data scientist with full-stack capability in a production environment.
• Ability to understand energy markets, grid dynamics, and trading strategies.
• Track record of taking projects from data exploration to production.
• Strong coding standards and production-quality software delivery.

Responsibilities

• Build, optimise, and deploy models that operate reliably at scale.
• Develop a deep understanding of energy markets, grid dynamics, and trading strategies.
• Own the full lifecycle of work, from research and prototyping through to production.
• Write clean, production-quality code and contribute to robust, scalable systems.
• Turn ideas out of notebooks into real-world, productionised solutions.

Skills

Full-stack data science

Python

React

Data exploration

Commercial mindset

Tools

Docker

GCP

Job description

About Us

At Axle Energy, we're building the infrastructure that will underpin the decarbonised energy system. Our software moves energy usage to times when electricity is cheap and green, by controlling vehicle charging, heating systems, and home batteries. We control hundreds of thousands of energy assets.

We're building in a legacy industry and moving gigawatt-hours of electrons in the real world, but we operate at lightning speed, and we're growing the team to meet customer demand.

We're proud to be supported by world-leading investors, including Energize Capital and Accel.

Read more about what we're building here.

About the role

We're hiring full stack data scientists who love to get into the nitty gritty of the domain, have an instinct for commercial value, and own the entire process from data exploration to production.

• Building, optimising, and deploying models that operate reliably at scale
• Developing a deep understanding of energy markets, grid dynamics, and trading strategies
• Taking ownership of the full lifecycle of your work, from research and prototyping through to production
• Writing clean, production-quality code and contributing to robust, scalable systems
• Working beyond notebooks, turning ideas into real-world, productionised solutions

It’d be nice if you could bring:

• Knowledge of the electricity system, specifically power trading
• Comfort speaking to clients (we're a small team and wear many hats)
• Familiarity with time-series data

Tech stack

We build in Python + React for the frontend (less relevant for this role)

Everything we build lives in Docker, for minimal cross-platform faff and maximal reproducibility.
Unlimited Claude Code tokens - we are aggressive users and explorers of AI, and encourage everybody to reconsider their workflows regularly

We deploy on GCP

What's in it for you

• A meaningful slice of equity in Axle, alongside a competitive salary, with total compensation ranging from £75k–£200k (base salary + equity).
• We operate with a deliberately flat structure and aim to keep pay equitable across the company, with a 1:1 median ratio between founder and team compensation.
• Enhanced parental leave to support you through life's meaningful moments.
• Bi-annual retreats to strengthen team connection & shared purpose.
• Hybrid working - We have a dog-friendly office around Farringdon. To maximize collaboration, we ask that you spend 2-3 days a week in the office.
• The opportunity to directly shape the future of energy markets and accelerate the transition to a low-carbon world.

We are extremely keen to build a diverse company, and we're particularly eager to hear from candidates who don't fit the traditional role stereotypes. If you're motivated by our mission, please do reach out, even if you feel you might not 'check all the boxes'.

Interview process

1. Initial interview
2. Take-home exercise
3. Final interview (in-person)
4. Offer, references, and welcome to the team!