Sanlam Life and Savings (SLS) is focused on serving our retail and corporate clients in South Africa and further developing our strategic advantages in the South African market. Sanlam Life and Savings consists of the following business units Retail Mass, Corporate, Risk and Savings, Glacier and various business enabling functions. The Sanlam Life and Savings Office provides strategic direction, coordination and support to the four clusters, as well as performing governance oversight that includes assurance provided by second line of defense functions in SLS, to enable us to meet our business objectives.
What will you do?
The experience investigations team is responsible for delivering business insights through retrospectively looking at claims and persistency experience. The team is also one of the few within the broader Sanlam Group to be a custodian of a Business Intelligence (BI) asset. The vision for the team is to fully digitalise our processes, and also to further enable consumption of new age statistical/actuarial techniques to add business value.
Output/Core Tasks: Manage, own and enhance the Experience Investigation reporting process within SRS/Glacier Actuarial to deliver valuable insights for the businesses that we serve
Collaborate to define, create and realise the ideal operating model for actuarial experience investigations in the context of a new business intelligence (BI) platform
Liaise and engage with stakeholders from Sanlam Group BI to ensure the efficient running of the experience investigations operation model
Ensure the Experience Investigation operating model delivers business value
Maintenance of the Experience Investigation model
Automation and optimisation of legacy processes
Assist with ad-hoc actuarial analyses on special projects
Collaborate in the wider SLS teams working on special projects
Regular engagement with senior management on the performance of the business
Deliver analytical-, business- or projection models as required from special projects
Research data science/statistical techniques and their application in an actuarial context
What will make you successful in this role?
Qualifications:
Qualified or nearly qualified actuary (FASSA)
3-4 years in the life insurance industry
Experience and skills:
Experience / knowledge of Sanlam's life insurance products will be an advantage
Leadership and managerial qualities
Python, R, SQL experience or knowledge of advanced analytics
Keen interest in advanced predictive modelling capabilities
Comfortable building and implementing statistical forecasting models
The combination of actuarial and data science experience will be an advantage
Comfort working with and interrogating big data sets
Strong operational process focus
Good verbal and written communication skills
Good attention to detail
Ability to work independently, take initiative and meet deadlines
Strong analytical and conceptual thinking
Good MS Office skills (Word, Excel)
Knowledge seeking/learning orientation
We're all about building strong, lasting relationships with our employees. We know that you have hopes for your future - your career, your personal development and of achieving great things. We pride ourselves in helping our employees to realise their worth. Through its five business clusters - Sanlam Fintech, Sanlam Life and Savings, Sanlam Investment Group, Sanlam Allianz, Santam, as well as MiWay and the Group Office - the group provides many opportunities for growth and development.
The shortlisting process will only start once the application due date has been reached. The time taken to complete this process will depend on how far you progress and the availability of managers.
Closing date: 20 September 2025
Our commitment to transformation
The Sanlam Group is committed to achieving transformation and embraces diversity. This commitment is what drives us to achieve a diverse, inclusive and equitable workplace as we believe that these are key components to ensuring a thriving and sustainable business in South Africa. The Group's Employment Equity plan and targets will be considered as part of the selection process.
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