At a Glance
- Tasks: Lead data science initiatives to drive commercial insights and product 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 dynamic team and mentor emerging data scientists.
- Why this job: Shape the future of energy efficiency while making a real impact.
- 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 - Hybrid employer: Oakmont Consulting
Join an innovative AI-driven energy tech scale-up in London, where you'll 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 making a significant impact on energy efficiency and sustainability. Enjoy a hybrid working model, competitive salary, and generous holiday allowance as you contribute to a mission that addresses one of the most pressing challenges in the built environment.
StudySmarter Expert Advice🤫
We think this is how you could land HEAD OF DATA SCIENCE - Hybrid
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those that demonstrate your ability to turn complex data into actionable insights. This will help you stand out and show how you can add value to the team.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the company's products. Be ready to discuss how your experience aligns with their goals, especially in reducing energy waste and improving operational performance.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the team and making an impact.
We think you need these skills to ace HEAD OF DATA SCIENCE - Hybrid
Some tips for your application 🫡
Show Your Passion for Data Science:Let us see your enthusiasm for data science in your application! Share specific examples of how you've used data to drive commercial outcomes or improve processes. This will help us understand your motivation and fit for the role.
Tailor Your CV and Cover Letter:Make sure your CV and cover letter are tailored to the Head of Data Science position. Highlight relevant experience with applied ML, Python skills, and any leadership roles you've had. We want to see how your background aligns with our needs!
Be Clear and Concise:When writing your application, keep it clear and to the point. Use bullet points where possible to make it easy for us to read. We appreciate straightforward communication, especially when it comes to complex topics like data science.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team at this exciting scale-up.
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 around 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.
✨Showcase Your Leadership Skills
As a potential head of a growing team, be prepared to talk about your mentoring style and how you've successfully led teams in the past. Highlight any experience you have in defining what 'good' looks like for analytics and how you've implemented best practices in your previous roles.
✨Prepare for Technical Questions
Expect some deep dives into your technical expertise, particularly around Python and building reproducible data science pipelines. Brush up on your knowledge of model evaluation and deployment practices, as these are key to ensuring your data science outputs become live product features.
