Company Description



PartnerRe is a leading, privately owned, multi-line global reinsurer with a reputation of financial stability and strength, and a commitment to rebuilding businesses and communities after risk events around the world.



Our mission is to continue to be a financially stable and predictable business partner, supporting our clients with solutions tailored to their needs, delivering superior returns to our owner, providing rewarding opportunities for our people and making a positive contribution to society. To achieve this, we live by our values of Integrity, Performance, Collaboration, Straightforward Communication and Respect and Care.



Core to The PartnerRe Experience is our global nature. No matter where you sit in the company, you are part of something bigger. Our teams represent our truly international mindset, forging connections across office locations and all levels of the organization and building a network of mutual success. The result is a day-to-day experience that will allow you to:




Shape your own career




Grow in a supportive environment




Connect with a community of experts




Make an impact



View Home - PartnerRe Experience e-book to find out more about what it's like to work at PartnerRe.




We are always looking for bright, proactive individuals to join our team!



Please follow our Careers page for all updates on new positions. We look forward to receiving your application.




PartnerRe is an equal opportunities employer.



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ABOUT THE ROLE



As a senior practitioner of data science, the position will report to the Global Head of Data Science Consulting within Life & Health, and should make a significant contribution to the enhancement of PartnerRe Life & Health's value proposition.




ABOUT YOU




Key responsibilities



Responsible for providing advice and expertise to internal and external clients, via:

• Consultative activities related to analysis of data


• Development & deployment of predictive models


• Import, wrangling and analysis of data to estimate targets associated with morbidity and mortality (and their drivers)


• Effective data driven storytelling through internal and external presentations and publications


• Research on the application of analytics to existing and new areas


• Development of self and others on analytic techniques

Technical skills/competencies

• Statistical & modeling skills normally acquired through graduate level education and post-graduate corporate experience.


• Ability to efficiently and effectively code in R (and Python)


• Practical experience in statistical analysis of data and predictive modeling using R.


• Breadth and depth are required (regression-like methods, modern ML (tree-based) methods, survival analysis, discrete data, etc.)


• Familiarity with Linux, SQL and/or Shiny is desirable


• Ability to work independently as well as support others

Soft skills

• The corporate language is English, but other languages are beneficial.


• The ideal candidate will be an excellent communicator, capable of working in a dynamic, culturally diverse international environment.


• They will be able to lead complex developments and projects independently.


• They will also be an effective team player ready to meet the business needs.

Work experience

• 5 years post graduate experience working in a related quantitative field.


• The ideal candidate will have worked extensively in the insurance industry.


• Life and/or Health insurance industry strongly desirable.


• (re)Insurance experience is a plus but not required.

Education / Professional qualifications or Designations

• At least an MS in a quantitative discipline.


• PhD in quantitative discipline is welcome.


• Qualifications and designations will be considered a plus.

Additional Information




#LI-Hybrid:



PartnerRe provides a working environment in which diversity is valued, where all employees feel welcome, respected, and empowered to perform at their best. We invite you to learn more about D&I at PartnerRe.



Thank you,



PartnerRe Hiring Team