Work Placement / Internship

Data and Analytics - Female Insight Week

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About you

  • Our Data & Analytics Female Insight Week is open to all undergraduates finishing university in 2023
  • We’re looking for people with a true passion for data and technology, and who enjoy problem-solving
  • You’ll be keen to develop new skills and perspectives, and channel your customer focus and problem-solving skills in an innovative environment.

We make the most of a changing world

The world, and the world of work in particular, is changing rapidly.

About the programme

This is a great way to learn more about our purpose, network with colleagues to hear about their experience, get a feel for our inclusive culture and what a career in this part of our business is all about.

The programme runs over five days in September 2021 (6th-10th).

You can expect to:

  • Learn about how we’re evolving to meet the opportunities and challenges of the future head-on, by networking with talented female colleagues in our Data teams
  • Broaden your professional horizons by meeting with key business leaders and graduates to get a feel for what a career in this part of our business is all about
  • See the difference data and analytics makes for our customers and how they interact with us through learning about the projects we are working on
  • Learn more about our Data Academy and how it can help you to continue building on your skills and master specialisms like data science and data engineering 
  • Understand more about our internship and graduate programmes and how these will help you forge a career in Data.

About the business area

Our data is one of our greatest assets, and how we harness it to understand the world, our business and our customers’ needs is crucial. In Data & Analytics, we promote the intelligent use of data and make sure it’s used in the right way.

Good data engineering helps us get to grips with the data we have. And data science allows us to apply statistics, computer science and problem solving skills together with strong research methods to test, learn and optimise machine learning powered decisions to help our customers.

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Job ID Number: #R-00121016
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