Job Detail

Adliswil, ZH, CH

Associate Data Scientist (80-100%) 

About Swiss Re

The Swiss Re Group 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. It anticipates and manages risk – from natural catastrophes to climate change, from ageing populations to cyber crime. The Swiss Re Group is organised into three Business Units, each with a distinct strategy and set of objectives contributing to the Group’s overall mission.

About the Role

Are you a PhD or MSc student with an interest in data science, artificial intelligence, machine learning, computing and mathematics? We're offering you the opportunity to utilize your studies as part of a paid, 3-6 month placement, where you'll gain hands on corporate exposure and experience of applying research techniques to a variety of real business projects.

What you will be doing

• In this role, you'll be part of a team of data scientists collaborating to build early prototypes, data-driven features and products


• Working closely with key members in Asset Management in identifying, analyzing and interpreting trends or patterns in complex financial data sets


• Current work stream of exposure might include the following:
  
  
  
  • Applying machine-learning methods for market and portfolio risk evaluation
  
  
  • Data analysis for recommender systems
  
  
  • Information Retrieval and Classification techniques for Research curation
  
  

About the Team

With more than USD 150 bn of assets under management, Swiss Re Asset Management manages the assets generated through the core insurance and reinsurance business. With the advent of technologies such as AI, Blockchain, RegTech or robotics the value chain of asset management will radically change in the future. The Smart Analytics team has a mission to prototype and deliver advanced analytics solutions using techniques ranging from statistical modelling, to machine learning and deep learning, serving stakeholders across the Asset Management value chain.

About You

• Working towards the completion of PhD or MSc studies in computer science/engineering, statistics, quantitative finance or any other computationally intense disciplines


• Strong passion for data science (modelling, data engineering and visualization)


• Hands-on programming experience with one or more of the following: Python, R, or related languages


• Keen interest in the financial markets and investment management


• Wish to explore and apply the latest techniques in statistical modeling, machine learning and deep learning in a financial context

Please apply with full documentation (CV, motivation letter, reference letters and diplomas/certificates)