Head of Data Science (Commercial Insights) Location: London (one day a week onsite) I’m working with an exciting AI-driven energy tech scale-up that’s using advanced analytics, machine learning and real-world electrical data to help commercial buildings dramatically reduce energy waste and improve operational performance.
They’re now looking for a Head of Data Science & Commercial Insights to join their leadership team and take ownership of how data science translates into real product value, customer impact and commercial outcomes.
This is a high-impact role sitting at the intersection of data science, product and commercial strategy – ideal for someone who wants to move beyond pure model-building and shape how analytics directly drives growth, sales and customer success.
The business is tackling one of the biggest inefficiencies in the built environment: wasted energy in heating, cooling and asset operation. Their platform turns high-frequency IoT and electrical data into actionable insight — helping customers identify inefficiencies, reduce consumption, and move toward predictive maintenance and ESG goals. They’ve recently secured further funding and are now scaling their data science capability into a core commercial function.
They need someone who can own the bridge between data science and commercial value, ensuring everything they build is useful, usable and used. Translate data science outputs into customer-facing insight, product features and commercial evidence Work closely with CTO, COO, Product, Engineering and Commercial teams Turn complex energy, HVAC and asset data into clear, trusted insight that drives decisions Lead and mentor a growing data science team (initially including 1 direct report) Help define what “good” looks like for analytics, dashboards and insight outputs
Applied ML on time-series / IoT / sensor / energy / building data Python (NumPy, pandas, scikit-learn, etc.) Building reproducible, well-tested data science pipelines Strong model evaluation, monitoring and deployment practices
Data science outputs consistently becoming live product features Clear commercial impact from analytics (sales, renewals, customer value) Reduced “ad hoc analysis” in favour of repeatable, scalable pipelines Strong applied ML background (ideally time-series / IoT / energy / industrial data) Proven ability to turn data science into product or commercial value Excellent Python skills and production-level engineering discipline Experience building and deploying ML pipelines in real environments Comfortable working with messy, high-volume real-world data 85,000 – £95,000 depending on experience~ Hybrid (London SE1) – minimum 1 day per week in office~28 days holiday + bank holidays~ Pension scheme~ Flexible working~ Training & development budget~ This is a chance to step into a role where data science is not a support function — it is the product . You’ll be shaping how a growing AI platform turns raw operational data into measurable energy savings, stronger customer outcomes and real-world climate impact….