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# Data Scientist

- **Company:** Zendo
- **Location:** Slough, UK
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Customer Data Management, Data Centers, Machine Learning
- **Published:** September 24, 2026
- **Apply:** https://www.collegerecruiter.com/job/2898594505-data-scientist

## About the Role

* MS or higher in statistics or machine learning, or equivalent experience (3-5 years in the, * 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., * 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.

## Description

* 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.


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