Data Scientist in City of London

AI is driving data center power consumption to more than double, from ~460 TWh today to a projected 1,000 TWh by 2030, roughly the electricity consumption of Japan! Hyperscalers and AI companies are racing to secure compute capacity, while new grid connections in key markets are queued years out. Meanwhile, capacity sits stranded in existing infrastructure, managed through outdated models that were never built to handle the power-dense workloads coming rapidly down the pike.

At Zendo we're developing the operating layer that enables operators to get more value from every watt. Our Energy OS platform brings together operational data, energy intelligence, and proprietary load forecasting across the data center power stack to help operators access more capacity, sooner.

We’ve been building at pace to match the urgency of the capacity crunch, with some great traction so far: Raised $2M+ in pre-seed funding from Fly Ventures, Pact, and Octopus Ventures, with angels from Google and across the data centre industry. Live with several UK data centre customers, with a pipeline to grow across the market. A founding team combining deep energy, B2B software, and data centre infrastructure expertise — ex-Octopus Energy, Square, Meta. This is an opportunity to join us on the ground floor, work directly with the founders, and grow with the business as we build Zendo into a true category leader on the frontlines of an industry undergoing the largest infrastructure build-out in history.

Your Role as Data Scientist: You'll work directly with our Founding Engineer (ex-Meta infrastructure) and the founders to build the data and modelling foundation at the core of Zendo's platform. You will own the full data lifecycle — from raw data centre data through to the predictive models powering capacity optimisation and the real-time economic model.

• Workload forecasting: improving Zendo's ability to predict data centre power demand accurately, building models that handle the complexity and variability of modern workloads.
• Capacity optimization models: sharpening the statistical rigour behind our capacity optimisation results, improving the quality and confidence of recommendations we deliver to operators.
• Real-time economic modeling: building a real-time economic model that connects capacity availability to commercial outcomes, unlocking workload optimisation capabilities.
• Model productionization: working with the engineering team to take models from development to production, ensuring they perform reliably on live customer data.

What We're Looking For:

• MS or higher in statistics or machine learning, or equivalent experience (3-5 years in the industry).
• Experience building and evaluating predictive models — you care about accuracy and know how to measure it properly.
• Strong time-series background — you've worked with high-frequency, real-world data that's messy and incomplete.
• Experience taking models to production, not just building them in notebooks.
• Comfort working in a small team where you own ambiguous ML problems end-to-end.
• Strong communication skills — you can explain model behaviour and uncertainty to non-technical stakeholders.

Nice to have:

• Understanding of electrical or mechanical systems, energy markets, or data center operations.
• Quantitative expertise or experience with economic modeling and real-time market bidding (e.g., simulated quant work, market making).
• Experience working in fast-paced delivery environments, proven experience building MVPs quickly and scaling later.

Beyond the CV:

• You're comfortable with ambiguity — the data won't always be clean and the problem won't always be well-defined.
• You think about the downstream commercial impact of your work, not just the technical output.
• You thrive in a 0→1 environment and take ownership end-to-end without waiting to be told what to do next.
• You're energised by working on a small team where your decisions have immediate, visible impact.

What We're Offering:

• A ground-floor, high-ownership role at a well-backed startup at one of the most exciting intersections in tech right now — AI compute and energy.
• Work directly with the founding team and a growing network of strategic advisors and investors.
• Access to a lovely co-working space in the heart of London’s Knowledge Quarter.
• Quarterly team offsites and socials.
• Competitive salary + equity.

Location & Requirements:

• Hybrid: We work 1–2 days/week from co-working spaces in London (King's Cross).
• Right to Work: You must have the legal right to work in the UK. We are unfortunately unable to sponsor visas at this time.

Ready to join the team? If you're excited about building the future of energy infrastructure for the AI era, we'd love to hear from you!