At a Glance
- Tasks: Design and build statistical models to drive marketing insights and strategies.
- Company: Join a leading energy company committed to a greener future.
- Benefits: Hybrid work, competitive pay, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and community impact.
- Why this job: Make a real impact on sustainable energy while developing your data science skills.
- Qualifications: Experience in Marketing Mix Modelling and strong Python skills required.
The predicted salary is between 36000 - 60000 £ per year.
Location: London, UK (Hybrid – approx. 1 day per week in office)
Contract: 6 Months (likely extension)
Join us. Be part of more. We’re more than an energy company — we’re a family of well-known brands transforming how we power the planet. As a team of over 20,000 colleagues, we’re driving a greener, fairer energy future by building a system that doesn’t rely on fossil fuels, while making a meaningful impact in the communities we serve. Here, you’ll find more purpose, more passion, and more potential.
About the Role
This role sits within a central Data Science function supporting multiple consumer-facing energy and smart home brands across the group. We’re looking for a highly analytical and detail-oriented Econometrics Manager / Data Scientist with hands-on experience in Marketing Mix Modelling (MMM), strong Python capability, and the ability to independently build robust statistical models (all essential). You will work closely with marketing teams, brand agencies, commercial teams, and senior stakeholders to gather data, build models, and deliver clear, actionable insights that influence strategic decision-making. A key part of this role is the ability to understand brand positioning, interpret brand language, and apply a customer-first mindset to ensure modelling outputs reflect real customer behaviour and support brand strategy.
Key Responsibilities
- Design, build, and maintain robust statistical and econometric models, including MMM frameworks
- Partner with marketing, brand, and commercial teams to gather and structure data required for modelling
- Work with agencies and internal stakeholders to ensure data accuracy, completeness, and alignment
- Develop models from scratch, selecting appropriate methodologies and validating outputs
- Translate complex model outputs into clear, actionable insights and recommendations for senior managers and decision-makers
- Apply a customer-centric lens to modelling, ensuring outputs align with brand positioning and customer behaviour
- Analyse large, complex datasets to quantify the impact of marketing activity on acquisition, retention, and engagement
- Apply advanced analytical techniques, including regression, machine learning, and time-series modelling using Python
- Communicate findings through compelling storytelling, presentations, and documentation
- Collaborate cross-functionally to scale and enhance modelling approaches using advanced statistical methods
Data Scientist employer: Pontoon Solutions
Join a forward-thinking energy company in London that prioritises sustainability and community impact, offering a collaborative work culture where your contributions truly matter. With a focus on employee growth, you will have access to continuous learning opportunities and the chance to work alongside passionate professionals dedicated to driving a greener future. Experience the unique advantage of a hybrid working model, allowing for flexibility while still fostering strong team connections.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨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 refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those involving Marketing Mix Modelling. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your Python skills and understanding econometric models. Be ready to discuss how you've applied these in real-world scenarios, as this will impress hiring managers looking for practical experience.
✨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 being part of our mission to drive a greener energy future.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Econometrics Manager / Data Scientist. Highlight your experience with Marketing Mix Modelling and Python, and don’t forget to showcase any relevant projects that demonstrate your analytical skills.
Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you’re the perfect fit for our team. Use it to explain how your background aligns with our mission of driving a greener energy future and how your skills can contribute to our goals.
Showcase Your Analytical Skills:In your application, be sure to mention specific examples where you've built robust statistical models or analysed complex datasets. We want to see how you’ve applied your skills in real-world scenarios, especially in marketing contexts.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity to join our family!
How to prepare for a job interview at Pontoon Solutions
✨Know Your Models Inside Out
Make sure you’re well-versed in Marketing Mix Modelling and other statistical techniques. Be ready to discuss your experience with building models from scratch, including the methodologies you’ve used and how you validated your outputs. This will show that you can hit the ground running.
✨Showcase Your Python Skills
Since strong Python capability is essential for this role, prepare to demonstrate your coding skills. Bring examples of projects where you’ve used Python for data analysis or model building. If possible, practice explaining your code and thought process clearly, as communication is key.
✨Understand the Brand's Voice
Familiarise yourself with the company’s brands and their positioning in the market. Think about how customer behaviour influences marketing strategies and be prepared to discuss how you would apply a customer-first mindset in your modelling work. This shows you’re not just a number cruncher but someone who understands the bigger picture.
✨Prepare for Storytelling
You’ll need to translate complex data into actionable insights, so practice how you would present your findings. Use storytelling techniques to make your insights compelling and relatable. Think about how you can engage senior stakeholders with your recommendations, as this will be crucial in influencing decision-making.
