Financial Data Scientist Intern

Vor 7 Tagen

Zürich, Zürich, Schweiz Swiss Re Vollzeit

Launch your career with Swiss Re as a Financial Data Scientist Intern Dive into exciting projects, support our teams, and apply your R coding skills and data analysis while working on real-world financial solutions.

About the Role

You will support the product areas in their regular responsibilities and deliverables and engage in project-based work. Most of the software development occurs in R with a setup RStudio and Shiny servers with DB connectivity through e.g. REST API, ODBC, ADO and, for collaboration on software projects, use of git for version control with repository hosting on Azure DevOps.

Some examples of things you could be working on:

  • Scenario impact on risk measures and balance sheet metrics using open-source or commercial frameworks
  • Supporting the management reporting process through execution and enhancement of current reports
  • Design and development of RShiny server dashboards
  • Analysis of embedded financial market risks within reinsurance transactions using the in-house libraries

This internship position is for three months of full-time work or can be extended to an equivalent of six months.

About the Team

Swiss Re is a leading global reinsurer, leveraging its expertise in risk to allocate capital to the most attractive and diversified risk pools while actively optimizing its asset and liability portfolio. The Market Risk Management (MRM) team is responsible for identifying, assessing, and mitigating financial market risks, such as interest rate, credit, and equity risks, that Swiss Re faces through its asset portfolio and embedded market risks in structured (re)insurance transactions and insurance-linked securities.

The MRM team operates in Zurich, London, New York City/Armonk, and Bangalore, and the role will engage with all three product areas within MRM: Credit & Equities, Treasury & Rates, and (Re)Insurance Transactions.

About You

Essential:

  • Master's or bachelor's student (at least six semesters completed) in quantitative subject (e.g., Mathematics, Computer Science, Engineering, Economics, Finance)
  • Solid coding skills in at least one major data language (Python and/or R)
  • Intellectual curiosity, drive and interest in financial and quantitative topics
  • Fully proficient in English

Nice to Have:

  • Prior professional (internship) experience with financial risk management (quantitative / market / credit etc), treasury or within asset management within the banking or (re)insurance sector

We are looking forward to your application

Due to immigration regulations non-EU/EFTA and UK citizens must provide a certificate from a Swiss university confirming that an internship is integral to their course of study. Kindly submit the mandatory letter from your university with your application documents.

We provide feedback to all candidates via email. If you have not heard back from us, please check your spam folder.


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. We cover both Property & Casualty and Life & Health. 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: 130029

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