Location: 

Zurich, Zurich, CH

Senior Analytics Engineer

Data & Analytics Reinsurance is a key tech partner for our Reinsurance divisions, supporting in the transformation of the data landscape and the creation of innovative analytical products and capabilities. We use modern approaches to managing the product lifecycle, design thinking and rapid prototyping to quickly test for value and ensure we build powerful insights and deploy them into production as part of analytical products. Both our team and our partners are spanning across different countries and serving a global customer basis. 
 
About The Role 
 
In your role as an Analytics Engineer in Data & Analytics Re, you collaborate with data engineers, business analysts and product owners to build impactful products tackling a variety of business challenges, such as improving our portfolio strategy, costing accuracy and financial performance. It is your responsibility to advise & support in product development as well as to implement sophisticated applications, reports, and dashboards by transforming data in pipelines, creating visualizations and simulation engines. Additionally, you will shape the Analytics Ontology, the go-to asset for self-service analytics and contribute to & run user training initiatives. 
 
Key Responsibilities 

 

  • Data Exploration & Consulting: Acting as a connector between business and data, advising on how best to use data and analytics to improve business outcomes 

  • Data Modelling: Building a user-centric data asset that is modelled around how our business understands the data 

  • Application Development & Data Visualization: Building impactful applications to support key business processes, with a focus on rapid prototyping & quick iterations 

  • Product Management: Apply core principles of product management throughout our deliverables to ensure that we deliver excellent products that fit the business needs 
     

About You 

 

In short, you're a product-minded engineer who loves working in cross-functional teams, delivering awesome data products quickly and constantly learning new things in the process! 

 

You should have: 

  • University degree with a quantitative background, 5+ years of data-related work experience in the Financial Industry, Consulting or Tech 

  • Strong ability to analyze data within the business landscape while applying conceptual and problem-solving skills 

  • Excelling in stakeholder management and ability to clearly communicate complex technical concepts. 

  • Experience in building applications and/or data visualizations 

  • Experience with Python & TypeScript 

  • Working knowledge of Palantir Foundry is preferred 

  • Experience with information modelling, understanding of data modelling concepts and working with data pipelines 

 

Nice To have: 

  • Hands-on experience with Apache Spark and a good understanding of distributed systems is a plus 

  • Experience in the (Re-)Insurance industry is a plus 

 

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.

 

 

Keywords:  
Reference Code: 128989 

 

 


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