This position is part of the US Experience Analysis department, which produces experience studies and analysis using internal and external data. A key goal of the department’s work is to identify and share key findings and insights about claims and persistency experience, and developing updates to best estimate assumptions or support other organizational needs as needed.

This position exists to help evaluate data from life reinsurance customers, as well as from the company’s own data, in order to analyze mortality and/or lapse experience for use in research and developing new best estimate assumptions. A key aspect of this position is to work closely with other team members as the team analyses experience data to understand the drivers for SCOR’s claims. These findings are then communicated to key company stakeholders so that the learnings can be reflected in business decisions and future assumptions. The position may also assist in building/modifying/implementing predictive models to assist in understanding our data and claims experience.

• Analyze emerging mortality, persistency, and other experience required to meet key strategic and organizational needs
• Analyze product, underwriting, or other company information for any influences on mortality from a historical or prospective perspective
• Help recommend assumptions for use in pricing and best estimate liability modeling
• Build, modify, and/or implement models for estimating/forecasting mortality and lapses.
• Optimize processes and tools to enhance procedures and approaches
• Perform regular inspection and maintenance of data supporting these studies
• Maintain a procedure for ensuring the accuracy of studies and summaries used in analysis
• Create and maintain SQL code for performing mortality and lapse studies on seriatim policy listings
• Create user-friendly extracts from mortality and lapse studies
• Other tasks as needed to accomplish the goals of the Experience Analysis department
• Duties in support of other actuarial functions of the company, as required

• Bachelor’s degree in Actuarial Science, Mathematics, Statistics, Data Analytics, Finance or related area.
• Minimum of two SOA exams passed
• High level of computer literacy with strong skills in MS Office, VBA, and Tableau
• Experience with large biometric data using SQL Server Management Studio, R, or Python.
• Solid mathematical and actuarial analysis skills with strong problem-solving ability
• Excellent verbal and written communication skills
• Strong collaboration skills
• Highly motivated/self-starter
• Must be able to work effectively as part of a team and independently with readiness to travel on occasion
• Regular attendance and ability to work extended hours as necessary to meet deadlines
Further regular progress towards the Educational Requirements for membership in the Society of Actuaries will be expected

As a leading global reinsurer, SCOR offers its clients a diversified and innovative range of reinsurance and insurance solutions and services to control and manage risk. Applying “The Art & Science of Risk,” SCOR uses its industry-recognized expertise and cutting-edge financial solutions to serve its clients and contribute to the welfare and resilience of society in around 160 countries worldwide.

Working at SCOR means engaging with some of the best minds in the industry – actuaries, data scientists, underwriters, risk modelers, engineers, and many others – as we work together to find solutions to pressing challenges facing societies.

As an international company, our common culture is defined by “The SCOR Way.” Serving both to build momentum that drives the Group forward and as a compass to guide our actions and choices, The SCOR Way is anchored by five core values, reflecting the input of employees at all levels of the Group. We care about clients, people, and societies. We perform with integrity. We act with courage. We encourage open minds. And we thrive through collaboration.

SCOR supports inclusion and the diversity of talents, and all positions are open to people with disabilities.