Our multi-disciplinary software, product, and data team serves as a central hub of digital expertise and innovation, supporting projects across the company. We work collaboratively with engineers, consultants and other specialists to use data and technology to solve real-world problems and improve the services we provide to our clients.

We have an opportunity for a Data Analyst/Scientist or Senior Data Analyst/Scientist to play a key role in using data, analytics, statistical methods and data science to generate insight, support decision-making and improve our engineering services.

This is a broad analytical role. You will work across the full lifecycle of a problem: understanding stakeholder needs, exploring and assessing data, identifying appropriate analytical approaches, communicating findings and, where appropriate, developing statistical or machine-learning models or client-ready insights/tools. This is a role for someone who enjoys variety and has a critical eye for finding the right solution for the problem. Sometimes this may be exploratory analysis, a dashboard or a set of clearly defined metrics; in other cases, it may involve forecasting, statistical modelling, machine learning or building/working with AI.

It's an exciting time to join our Digital team. Working alongside a range of specialist engineers and consultants, you will be joining a collaborative, knowledgeable, highly engaged team, and offer a supportive, flexible, and high-performing work culture. In a time where building and energy resilience is ever more important, we are driving forward innovation to make an impact with data and technology.

You will have the opportunity to engage in a variety of high-impact projects, working on challenging problems for some of the UK’s most notable organisations, including the NHS and Oxford University. Our team has recently worked on creating data science-led for managing estates in hospitals, building energy forecasting models, and harnessing data on building performance to create better designed buildings of the future.

In this key and varied role, you can expect to:

• Work with engineers, consultants, product teams and other stakeholders to understand their needs and translate sometimes ambiguous questions into well-defined analytical problems.
• Develop and implement data-driven solutions to solve real-world business problems across the company.
• Use SQL, Python and other analytical tools to investigate datasets, identify trends and relationships, test hypotheses and generate actionable insights.
• Apply appropriate statistical techniques, forecasting methods, ML and AI approaches where they add value to the problem being solved.
• Collaborate with the product and software engineering teams to turn analytical work into reusable tools, workflows and data-driven products where appropriate.
• Develop reproducible and maintainable analytical code, following best practices, including version control, testing, and peer reviews.
• Contribute to the development of analytical and data science capability across the business by sharing approaches, reusable methods and good practice
• 
  

Our multi-disciplinary software, product, and data team serves as a central hub of digital expertise and innovation, supporting projects across the company. We work collaboratively with engineers, consultants and other specialists to use data and technology to solve real-world problems and improve the services we provide to our clients.

We have an opportunity for a Data Analyst/Scientist or Senior Data Analyst/Scientist to play a key role in using data, analytics, statistical methods and data science to generate insight, support decision-making and improve our engineering services.

This is a broad analytical role. You will work across the full lifecycle of a problem: understanding stakeholder needs, exploring and assessing data, identifying appropriate analytical approaches, communicating findings and, where appropriate, developing statistical or machine-learning models or client-ready insights/tools. This is a role for someone who enjoys variety and has a critical eye for finding the right solution for the problem. Sometimes this may be exploratory analysis, a dashboard or a set of clearly defined metrics; in other cases, it may involve forecasting, statistical modelling, machine learning or building/working with AI.

It's an exciting time to join our Digital team. Working alongside a range of specialist engineers and consultants, you will be joining a collaborative, knowledgeable, highly engaged team, and offer a supportive, flexible, and high-performing work culture. In a time where building and energy resilience is ever more important, we are driving forward innovation to make an impact with data and technology.

You will have the opportunity to engage in a variety of high-impact projects, working on challenging problems for some of the UK’s most notable organisations, including the NHS and Oxford University. Our team has recently worked on creating data science-led for managing estates in hospitals, building energy forecasting models, and harnessing data on building performance to create better designed buildings of the future.

In this key and varied role, you can expect to:

• Work with engineers, consultants, product teams and other stakeholders to understand their needs and translate sometimes ambiguous questions into well-defined analytical problems.
• Develop and implement data-driven solutions to solve real-world business problems across the company.
• Use SQL, Python and other analytical tools to investigate datasets, identify trends and relationships, test hypotheses and generate actionable insights.
• Apply appropriate statistical techniques, forecasting methods, ML and AI approaches where they add value to the problem being solved.
• Collaborate with the product and software engineering teams to turn analytical work into reusable tools, workflows and data-driven products where appropriate.
• Develop reproducible and maintainable analytical code, following best practices, including version control, testing, and peer reviews.
• Contribute to the development of analytical and data science capability across the business by sharing approaches, reusable methods and good practice
•