Millions of people are relying on us to develop better medicines to treat their disease and innovations in the way they take their medicine. Our biostatisticians and statistical programmers play an important role in our success.
From providing insights that help in the planning and design of clinical trials, to conducting statistical analyses and reporting results when they are finished, we depend on our biostatisticians and statistical programmers.
Our biostatistics team is 250 people strong and split - approximately 50:50 - between statisticians and programmers. They are mostly in Denmark and India, but there are smaller teams in China and Japan as well.
Meet Henning and Randi below and learn more about biostatistics, the work we do and our future aspirations. See if it is the right team for you!
Our biostatisticians and statistical programmers follow the trends in the industry, and apply state-of-art statistical methodology while also contributing to scientific communities.
Working alongside stakeholders from across the organisation, biostatisticians design clinical trials, including calculation of sample sizes and selection of statistical methodology.
They also conduct the statistical analyses and interpret the data for submissions to authorities and scientific papers. Biostatisticians often co-author articles for scientific journals, outlining the clinical development programme and establishing its credibility in the market.
To ensure the continued development of the biostatistical expertise, we regularly hold internal and external scientific meetings and focus groups.
We expect our biostatisticians to have either a Master or a PhD in Statistics. The role requires a strong background in mathematical statistics and a sound theoretical foundation is essential, along with a good knowledge of how to apply statistical models.
Statistical programmers can come from more diverse backgrounds than biostatisticians, but should either have a Master or a PhD in natural or computer science. They need to be fluent in one of the major programming languages and must have a solid understanding of data and strong analytical skills.