Join Centrica as a Data Scientist in a full-time, flexible role that is predominantly home-based with occasional visits to the Cardiff site. You will use data science and machine learning to tackle complex business challenges and drive measurable outcomes.
Requirements
Experience applying statistical analysis and machine learning to real-world business problems.
Strong programming skills in Python and SQL.
Experience with or exposure to PySpark and Databricks.
Knowledge of production ML practices such as Git, CI/CD, and MLflow.
Experience in customer analytics or utilities is beneficial but not essential.
Skills & Responsibilities
Python and SQL: Analyse large and complex datasets to identify patterns, opportunities, and drivers of customer behaviour.
Machine Learning: Design, build, test, and deploy statistical and machine learning models for churn, retention, and propensity modelling.
PySpark and Databricks: Build robust feature engineering, training, and inference pipelines using scalable technologies.
Production ML practices: Take models into production through automated workflows, testing, version control, and model lifecycle management.
Potential transition routes: People from Data Analyst or Software Engineer roles may bring analytical thinking and programming skills, alongside meeting technical requirements.
Job description
Join us, be part of more.
We’re so much more than an energy company. We’re a family of brands revolutionising how we power the planet. We're energisers. One team of 21,000 colleagues that's energising a greener, fairer future by creating an energy system that doesn’t rely on fossil fuels, whilst living our powerful commitment to igniting positive change in our communities. Here, you can find more purpose, more passion, and more potential. That’s why working here is #MoreThanACareer. We do energy differently - we do it all. We make it, store it, move it, sell it, and mend it.
We have an exciting opportunity for a Data Scientist to join our team, using relevant data to tackle complex business challenges and turn insight into measurable outcomes.
You'll work across a varied portfolio of customer, commercial and operational problems, from understanding churn and retention to Customer Lifetime Value (CLTV), segmentation, propensity modelling and operational optimisation.
This is more than a model-development role. You'll have the opportunity to build reusable, production-ready solutions, embed models into business processes and see the real-world impact of your work.
Key Accountabilities:
Design, build, test and deploy statistical and machine learning models to solve customer, commercial and operational challenges.
Analyse large and complex datasets to identify patterns, opportunities and drivers of customer behaviour, translating your findings into clear, actionable recommendations.
Partner with stakeholders to turn commercial questions and opportunities into well-defined data science problems.
Develop solutions across areas including churn and retention, CLTV, segmentation, propensity modelling, customer targeting and optimisation.
Build robust feature engineering, training and inference pipelines, using technologies such as Python, PySpark and Databricks.
Help take models into production through automated workflows, testing, version control, CI/CD, monitoring and model lifecycle management.
Collaborate with data engineers, platform teams and fellow data scientists to create scalable, reliable solutions while maintaining high standards of data quality, model governance and responsible AI.
Here’s what we’re looking for:
Experience applying statistical analysis and machine learning to real-world business problems.
Strong programming skills in Python and SQL, with experience working with large and complex datasets.
Experience with, or exposure to, PySpark and Databricks.
A good understanding of machine learning techniques, which could include classification, regression, gradient boosting/XGBoost, segmentation, propensity modelling or survival analysis.
Experience or knowledge of production ML practices such as Git, CI/CD, MLflow, automated testing, model deployment and monitoring.
Strong analytical thinking, with the ability to take an ambiguous business question through exploration and modelling to an actionable recommendation.
The ability to explain complex analytical approaches, assumptions and results clearly to both technical and non-technical audiences.
A collaborative and curious approach, with a willingness to learn, challenge existing thinking and share knowledge.
Experience within customer analytics, energy, utilities, retention, pricing or commercial analytics would be beneficial, but isn't essential.
Location:
We operate a Flexible First approach, giving colleagues flexibility in how and where they work. This role can be predominantly home-based, although ideally you will be based within commutable distance of our Cardiff site and be flexible to travel across our sites as may be needed on occasion for team meetings.
Why should you apply?
We’re not a perfect place – but we’re a people place. Our priority is supporting all of the different realities our people face. Life is about so much more than work. We get it. That’s why we’ve designed our total rewards to give you the flexibility to choose what you need, when you need it, making sure that you and your family are supported not only financially, but physically and emotionally too. Visit the link below to discover why we’re a great place to work and what being part of more means for you.
If you're full of energy, fired up about sustainability, and ready to craft not only a better tomorrow, but a better you, then come and find your purpose in a team where your voice matters, your growth is non-negotiable, and your ambitions are our priority.
Help us, help you. We would love for you to share any information about yourself throughout our recruitment process so that we can better understand you and help shape your journey.
