At a Glance
- Tasks: Lead data science initiatives to transform energy data into actionable insights and commercial value.
- Company: Exciting AI-driven energy tech scale-up focused on reducing energy waste.
- Benefits: Competitive salary, hybrid work model, 28 days holiday, and growth opportunities.
- Other info: Join a growing team and mentor others while tackling energy inefficiencies.
- Why this job: Shape the future of energy efficiency while driving real impact in a dynamic environment.
- Qualifications: Strong background in applied ML, Python skills, and experience in commercial data science.
The predicted salary is between 85000 - 95000 £ per year.
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
Key requirements include:
- 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
Salary: £85,000 – £95,000 depending on experience. Hybrid (London SE1) – minimum 1 day per week in office. 28 days holiday +
Head of Data Science - Energy employer: Oakmont Consulting
Join an innovative AI-driven energy tech scale-up in London, where you will play a pivotal role in transforming data science into tangible commercial value. With a strong focus on employee growth and a collaborative work culture, this company offers unique opportunities to lead a dynamic team while contributing to sustainability goals in the built environment. Enjoy a competitive salary, generous holiday allowance, and the flexibility of hybrid working, making it an excellent choice for those seeking meaningful and impactful employment.
StudySmarter Expert Advice🤫
We think this is how you could land Head of Data Science - Energy
✨Tip Number 1
Network like a pro! Reach out to people in the energy tech space, especially those who work with data science. Attend industry events or webinars, and don’t be shy about sliding into DMs on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Showcase your skills! Create a portfolio that highlights your best projects, especially those involving applied ML and real-world data. Make sure it’s easy to navigate and visually appealing. This will help you stand out when you’re chatting with potential employers.
✨Tip Number 3
Prepare for interviews by practising common questions related to data science and commercial insights. Think about how you can translate complex data into actionable insights. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of exciting opportunities, and applying directly can sometimes give you an edge. Plus, it shows you’re genuinely interested in being part of our team!
We think you need these skills to ace Head of Data Science - Energy
Some tips for your application 🫡
Show Your Passion for Data Science:Let us see your enthusiasm for data science and how it can drive commercial value. Share specific examples of how you've turned complex data into actionable insights in your previous roles.
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with applied machine learning, especially in energy or IoT contexts. We want to see how your skills align with our mission to reduce energy waste.
Highlight Leadership Experience:Since this role involves mentoring a growing team, don’t forget to showcase any leadership or mentoring experiences you’ve had. We’re looking for someone who can inspire and guide others in the data science field.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensure it gets the attention it deserves. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Oakmont Consulting
✨Know Your Data Science Stuff
Make sure you brush up on your applied machine learning skills, especially in time-series and IoT data. Be ready to discuss how you've turned complex data into actionable insights in previous roles. This is crucial for showing that you can bridge the gap between data science and commercial value.
✨Understand the Business Impact
Familiarise yourself with how data science can drive growth and customer success in the energy sector. Think about specific examples where your work has led to measurable commercial outcomes. This will help you demonstrate your ability to translate data outputs into real-world value.
✨Show Off Your Team Leadership Skills
Since this role involves leading a growing data science team, be prepared to talk about your mentoring experience. Share examples of how you've guided others in building reproducible data science pipelines or improving model evaluation practices. This will highlight your leadership capabilities.
✨Prepare for Technical Questions
Expect some technical questions around Python and data science tools like NumPy and pandas. Brush up on your knowledge of building and deploying ML pipelines, and be ready to discuss your approach to handling messy, high-volume data. This will show that you're not just a theorist but someone who can get things done in a real environment.
