In times of growing volatility and uncertainty, the ability to identify future trends has never been more important. Are you eager to learn and understand more about the medical, healthcare, societal and lifestyle factors that drive long-term changes in the global insurance industry? A highly motivated and curious person, you would help us as we investigate a wide range of topics from the individual outcomes of health forecasting to mortality research, cancer & heart attack rates and the COVID-19 pandemic.
Note, that this is a 10-week internship with an expected start date on 24th of June 2024.
About the role
This position would suit a person who is looking to bring their knowledge of life and/or data science, analysis and current trends into a fast-paced business with a real-world impact. This job will involve extensive R&D. You will apply your quantitative and qualitative analytical skills to the latest research trends impacting medical science. After analysing results, you would help us to communicate this to a wide range of audiences, both internally and externally. You would be expected to draft substantial amounts of text for publications or presentations, alongside producing graphics/graphs/visualisations.
You will be expected to work independently but will of course have support and mentorship from the project coach and project sponsor and learn from others in the team as well.
About the team
The Life Research and Forecasting team at Swiss Re is an international multidisciplinary research group across Europe and Asia, comprised of 6 post-PhD scientists (medical, life and computer science) and headed by an experienced pricing actuary. The team works on a broad range of topics such as mortality developments, cancer rates, ageing, COVID-19, and advancement in medicines & technology.
We use our expert knowledge to consult on core trends in healthcare. We identify and analyse structured/unstructured datasets throughout the world that provide insights on health trends and developments. We establish effective partnerships and collaborations with universities, data providers and research organisations on a global basis.
About You
• You must hold or be in the process of completing PhD or be a highly experienced MSc, MPH, or equivalent degree holder or student.
• Your studies will likely be in the life/medical sciences, biomedical research, epidemiology or medical statistics.
• You have excellent qualitative & quantitative analytical skills, including Excel (Python, R etc are a plus)
• You are confident communicator with excellent oral & written English & presentation skills. Substantial written communications experience is a plus – both academic publications and/or commercial science.
• You have already gained some experience or understanding of the medical, societal and lifestyle drivers that impact morbidity/mortality, which would be highly preferable.
• You are comfortable working in a team and independently, with experience in managing, prioritising and time management of multiple tasks. #LI-Hybrid
About Swiss Re
Swiss Re is one of the world’s leading providers of reinsurance, insurance and other forms of insurance-based risk transfer, working to make the world more resilient. We anticipate and manage a wide variety of risks, from natural catastrophes and climate change to cybercrime. Combining experience with creative thinking and cutting-edge expertise, we create new opportunities and solutions for our clients. This is possible thanks to the collaboration of more than 14,000 employees across the world.
Our success depends on our ability to build an inclusive culture encouraging fresh perspectives and innovative thinking. We embrace a workplace where everyone has equal opportunities to thrive and develop professionally regardless of their age, gender, race, ethnicity, gender identity and/or expression, sexual orientation, physical or mental ability, skillset, thought or other characteristics. In our inclusive and flexible environment everyone can bring their authentic selves to work and their passion for sustainability.
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Reference Code: 128738
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