Skip to main content Skip to job search
No going back: We're reimagining our world of work. Colleagues who were office-based can now ‘locate for their day’. Meet at a 'hub' office, work from home or somewhere else. The choice is yours! Find out more >

Data Science Jobs & Careers

Realising the opportunities presented by Big Data

Data Science Jobs & Careers

Our team

We're changing how data is used to drive decisions, empowering our colleagues to better support the ever-changing needs of our 15 million members. With Data now at the heart of everything we do, we’re increasing our capabilities and are looking for data scientists who can solve some of our most challenging business problems.


What we do

We use Data Science techniques to support colleagues in delivering value for Nationwide and our members, identifying opportunities to generate income, reduce costs and maintain legendary service.

We’re always looking for exceptional people. Fill in your details below and we’ll keep in touch

Get in touch
Data Cleansing

Building Capacity – The Architecture of Data Science

Data Science is attracting attention. Across the world, the need to marry the nuances of statistics with the discipline of programming is recognised as key to improving customer service and keeping pace with changes in markets.
A survey in 2016 concluded that 80% of Data Science is preparing and cleansing data (the 80/20 rule). That survey of Data Scientists became perceived wisdom and a widely recognised problem statement for Data Science.

This is a key issue for any implementation of Data Science. How to provide an architecture that works to minimise this problem is at the heart of any decision made.

Architectural Challenges

From a Data Scientist perspective, it’s not important what actual technology is employed. This is because the models and algorithms that are used are defined mathematically. Therefore, the trusted source of truth is the mathematical definition of the algorithm.

However, for non-functional requirements, this is not as straightforward. For example, the availability and cost of experts for a certain programming language and technology varies heavily. When it comes to maintenance, the chosen technology has a major impact on a project’s success.

Therefore, the challenge is to provide a platform with high interoperability at minimum cost. Choices over selecting a stack of technology by the same vendor as opposed to bringing in “best in class” products for specific functions have to be keenly evaluated.
The benefits of a stacked approach should outweigh those cons of employing separate systems that will need further work to make them integrated.


Another challenge of Data Science tooling is around how to productionise systems and processes where there is a high proportion of proof of concept (PoC) working or hackathons. When it comes to industrialisation and enterprise projects, architectural guidance on technology usage must be in place.

Knowledge Management

Data scientists are great innovators. They are usually able to rapidly progress to a solution without necessarily having non-functional requirements (NFRs) such as scalability and maintainability in mind. Therefore, there is a need for an architectural framework to underpin their work and ensure that NFRs are properly addressed.
Building Capacity

Data science can work well with Agile methods of project management. Prototyping and rapid development means that the discipline can flourish within an Agile environment.


Sounds interesting? At Nationwide Building Society, we are invested in listening to our members and making changes to improve our service to them. This can be amazingly rewarding. Being able to save members time and money is key to what we do.

Data Scientists find insight and, at Nationwide, we are enriching our data enabled capability, with Data Scientists supporting the ways in which we can make our service to members even better and reduce our costs in the process.

Check out our jobs and see if helping our members with Data Science at Nationwide is for you.


Using Big Data

The world is a noisy place with constant interactions producing mountains of structured and unstructured data, aptly called Big Data. Data Scientists use their expertise and cutting-edge technology to draw actionable insights from this Big Data and Nationwide has put in place an infrastructure to support them. Senior Business Intelligence Manager Graeme Reed explains.

Rewarding our members

Data scientists commonly find that insights are not used in decision-making, but at Nationwide we are enriching our data enabled capability, with Data Science supporting core business decisions. Investing in listening to our members and analysing how they prefer to do business with us means we can make developments that save them time and money, which is key to what we do as a Society and rewarding for us. 

Rising to the challenge

Challenges for Data Scientists can be around the data itself, including how 'dirty' it is, its availability as well as privacy issues. Our Data & Analytics Community has expanded its Data Quality capability to ensure that issues are addressed at an early stage of the data life cycle.

We all need the right tools for the job too, and we have a slice of the £4 billion investment in tech announced recently. We're ensuring tooling for key technical activities is robust and up-to-date, with for example Hive Hadoop and Python3 being rolled out across the business.

Nationwide has a clear Data Strategy that recognises the importance of Data Science and has a clear direction to go in with the available data.

We'll continue to put insight from data at the forefront of business decisions. If you want to join us, check out our vacancies or get in touch via the start a conversation form above.