We’re hiring data scientists who get into the weeds, ship delightful software, and want to step into the arena in the fight against climate change. We’re building the software infrastructure for the decarbonised energy system, backed by some of the best investors in the world (<a href="https://techcrunch.com/2024/08/01/axle-energys-sprint-to-decarbonize-the-grid-lights-up-with-9m-seed-led-by-accel">TechCrunch</a>).We make the technology to move energy usage to times when electricity is cheap and green. Our software controls vehicle charging, heating systems, and home batteries. We use machine learning to figure out what energy people will need, and when they'll need it. We control tens of thousands of energy assets, and we’re growing quickly.Read more about what we’re building <a href="https://www.axle.energy/blog/analysis/power-of-the-home">here</a>.RequirementsYou can expect:<ul> <li>insane amounts of ownership</li> <li>hard technical challenges</li> <li>that what you build is commercially and environmentally valuable</li> </ul> In return, we ask for:<ul> <li>the courage to build new things fast</li> <li>a commitment to real world impact over technical perfection</li> <li>a desire to help build and lead an exceptional and tight knit team</li> <li>deep-seated motivation to combat climate change</li> </ul> And it’d be nice if you could bring:<ul> <li>knowledge of the electricity system, specifically power trading</li> <li>comfort speaking to clients (we’re a small team and we all wear many hats)</li> <li>familiarity with time-series data</li> </ul>You shouldn't apply if:<ul> <li>uncertainty scares you</li> <li>you aren't prepared to try, fail, and try again</li> <li>you're looking for a low intensity, low impact role </li> </ul>Interview process<ol> <li>Initial interview</li> <li>Take-home exercise</li> <li>Final interview (in-person)</li> <li>Offer, references, and welcome to the team!</li> </ol><h3>Tech stack</h3>🐍 We do everything in Python, because it allows data scientists and engineers to collaborate closely and move quickly. Our data scientists write lots of production code. We ❤️ Streamlit.🎨 We try a bunch of things in Figma before we build them in code, because it's a fast and cheap way to get feedback.🐋 Everything we build lives in Docker, for minimal cross-platform faff and maximal reproducibility.☁️ We deploy on GCPBenefitsWe love the idea of fully remote work but it doesn't… work. For very early stage companies, people learn faster, get on better, and accomplish more when they're spending a decent chunk of time together. We ask that you spend 2-3 days a week in our London office.We are extremely keen to build a diverse company, and we’re particularly eager to hear from candidates who don't fit the traditional engineering stereotypes. If you’re motivated by our mission, please do reach out, even if you feel you might not ‘check all the boxes’.

We build software to move energy usage to times when electricity is cheap and green. Think of it as the operating system for a decarbonized grid.We integrate home energy devices into electricity markets to earn consumers money. Our software controls vehicle charging, heating systems, and home batteries. We use machine learning to figure out what energy people will need, and when they'll need it. We minimize CO2 and costs, and protect the grid by limiting peak demand.We've raised &gt;$10m in funding and in our first 2 years we've connected to &gt;100k devices in the UK alone. Join us to decarbonize the grid.

Data Scientist

We’re hiring data scientists who get into the weeds, ship delightful software, and want to step into the arena in the fight against climate change. We’re building the software infrastructure for the decarbonised energy system, backed by some of the best investors in the world (<a href="https://techcrunch.com/2024/08/01/axle-energys-sprint-to-decarbonize-the-grid-lights-up-with-9m-seed-led-by-accel">TechCrunch</a>).We make the technology to move energy usage to times when electricity is cheap and green. Our software controls vehicle charging, heating systems, and home batteries. We use machine learning to figure out what energy people will need, and when they'll need it. We control tens of thousands of energy assets, and we’re growing quickly.Read more about what we’re building&nbsp;<a href="https://www.axle.energy/blog/analysis/power-of-the-home">here</a>.RequirementsYou can expect:<ul> <li>insane amounts of ownership</li> <li>hard technical challenges</li> <li>that what you build is commercially and environmentally valuable</li> </ul> In return, we ask for:<ul> <li>the courage to build new things fast</li> <li>a commitment to real world impact over technical perfection</li> <li>a desire to help build and lead an exceptional and tight knit team</li> <li>deep-seated motivation to combat climate change</li> </ul> And it’d be nice if you could bring:<ul> <li>knowledge of the electricity system, specifically power trading</li> <li>comfort speaking to clients (we’re a small team and we all wear many hats)</li> <li>familiarity with time-series data</li> </ul>You shouldn't apply if:<ul> <li>uncertainty scares you</li> <li>you aren't prepared to try, fail, and try again</li> <li>you're looking for a low intensity, low impact role </li> </ul>Interview process<ol> <li>Initial interview</li> <li>Take-home exercise</li> <li>Final interview (in-person)</li> <li>Offer, references, and welcome to the team!</li> </ol><h3>Tech stack</h3>🐍 We do everything in Python, because it allows data scientists and engineers to collaborate closely and move quickly. Our data scientists write lots of production code. We ❤️ Streamlit.🎨&nbsp;We try a bunch of things in Figma before we build them in code, because it's a fast and cheap way to get feedback.🐋&nbsp;Everything we build lives in Docker, for minimal cross-platform faff and maximal reproducibility.☁️&nbsp;We deploy on GCPBenefitsWe love the idea of fully remote work but it doesn't… work. For very early stage companies, people learn faster, get on better, and accomplish more when they're spending a decent chunk of time together. We ask that you spend 2-3 days a week in our London office.We are extremely keen to build a diverse company, and we’re particularly eager to hear from candidates who don't fit the traditional engineering stereotypes. If you’re motivated by our mission, please do reach out, even if you feel you might not ‘check all the boxes’.

Data Scientist

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About the Company

Axle Energy

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