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Data Science is multi-disciplinary field that provides an opportunity to develop a wide range of skills. This new placement offers the chance to help the Statistical Data Sciences (SDS) team to solve real-world business problems and assist in our objective to upskill the wider Biostatistics community in Data Science.
You will primarily work in R, but you will be exposed to multiple programming languages, tools and technologies during this placement. As part of a small but multiskilled team you will work on both large and small projects helping to create tools and applications that will assist statisticians, statistical programmers and scientists in their everyday work. In addition, you will support our Data Science upskill objective by generating training materials, investigating new tools and methods, contributing to our blogs and helping to run the Data Science community.
Further opportunities may include the implementation and evaluation of predictive modelling approaches, including both Statistics and Machine Learning models.
Exposure to the R language and tools such as Git are helpful but much of the required training is provided during the placement. Above all you will need strong communication skills, enjoy writing code and be eager to learn and try new things.
You should be on track for a 2.2 (or above) in a degree with a strong background in Data Science, Statistics, Mathematics or related Discipline.
You will have completed a minimum of 2 years of your undergraduate degree but will not have graduated at the start of your placement. You will be expected to provide evidence from your university to show you will be an undergraduate student for the duration of the placement year.
The Assessment Centre for successful applicants is expected to take place in November 2019.
We recruit on an on-going basis and prioritise applications based on the application date.
Applications will closed when we have filled our assessment centre dates.