Head of Data Science (Commerical Insights)

Head of Data Science (Commercial Insights)

Location: London (one day a week onsite)

Salary: up to £95,000

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 Mission

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.

🚀 The Role

This is not a research-only leadership position. They need someone who can own the bridge between data science and commercial value, ensuring everything they build is useful, usable and used.

You will:

• Translate data science outputs into customer-facing insight, product features and commercial evidence
• Shape the roadmap around real customer problems and business priorities
• 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 delivery from prototype → production → scalable product capability
• Ensure models are robust, deployed, monitored and maintainable
• Lead and mentor a growing data science team (initially including 1 direct report)
• Support customer pilots, demos, investor updates and proof-of-value work
• Help define what “good” looks like for analytics, dashboards and insight outputs

🧠 Technical & Delivery Focus

You’ll still be hands-on and expected to lead by example technically, including:

• Applied ML on time-series / IoT / sensor / energy / building data
• Python (NumPy, pandas, scikit-learn, etc.)
• Productionisation of models into scalable workflows
• MLOps practices (e.g. MLflow, Airflow / Prefect, Docker)
• Building reproducible, well-tested data science pipelines
• Working with noisy, real-world operational datasets
• Strong model evaluation, monitoring and deployment practices

📈 What Success Looks Like

• 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 customer-facing insight used in demos, pilots and reporting
• A high-performing DS function that is both technically credible and commercially sharp

👤 What They’re Looking For

• 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
• Strong communicator - able to translate complex outputs clearly
• Experience in small, fast-moving teams or scale-ups
• Leadership experience (or clear readiness to step into it)

📍 The Package

• £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
• Equipment provided
• Opportunity to shape a core function in a scaling business

💬 Why This Role?

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.

For more information, please contact Hannah from Oakmont Consulting