Data Scientist

About the Position/ Overall Summary:

As a 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

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

Behavioural Competencies:

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, but 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:

- At least an MS in a quantitative discipline

- PhD in quantitative discipline is welcome