Uniting science, technology and talent to get ahead of diseases together. GSK is a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together – so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns – as an organization where people can thrive. We prevent and treat disease with vaccines, specialty and general medicines. We focus on the science of the immune system and the use of new platform and data technologies, investing in four core therapeutic areas (infectious diseases, HIV, respiratory/ immunology and oncology). Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it’s also about making GSK a place where people can thrive. We want GSK to be a place where people feel inspired, encouraged and challenged to be the best they can be. A place where they can be themselves – feeling welcome, valued, and included. Where they can keep growing and look after their wellbeing. So, if you share our ambition, join us at this exciting moment in our journey to get Ahead Together. ViiV Medical Affairs Insights and Analytics provides a critical function within the organization by connecting the insights and strategies of the central brand teams with the needs of the Medical field teams. The team is responsible for the following: 1) Ensuring that ViiV Medical audience design is objective and reflects scientific needs of the HIV and HIV prevention communities, 2) Leverages advanced analytic methodologies to better predict and optimize future field resources and engagements, 3) Translates HCP engagements into performance/impact metrics and dashboards that will drive business decisions, and 4) Creates tools for the field that enable them to plan engagements more strategically and efficiently. The Medical Affairs Advanced Analytics Intern will be responsible for enhancing two existing analytical models: Converting a currently static model that clusters customers into distinct segments into a dynamic model that routinely measures customer shifts in segments over time with a high degree of accuracy. The model must include a means for ascertaining model fit over time, to identify vulnerabilities in the model which will require adjustment to maintain high degree of accuracy. Converting a currently static pathway model into a flexible pathway model where channel engagements can be updated with new data sources as they become available.
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Job Type
Full-time
Career Level
Intern
Number of Employees
5,001-10,000 employees