Since our establishment in 1918, Sanlam has been a prominent part of the South African business landscape. We have always held a long-term view of how business adapts to the demands of the environment in which it operates. Today, in a dynamic world, we see an evolving set of social, economic, political and environmental imperatives that require our skilful response. For us at Sanlam, sustainable business practice means recognising both our broader responsibilities as an organisation in society, and the new opportunities that arise from this thinking. Our Vision is: To be the leader in client-centric wealth creation, management, and protection in South Africa; To be a leading Pan-African financial services Group with a meaningful presence in India and South-East Asia; and To play a niche role in wealth and investment management in specific developed markets. Our Values are: Acting with integrity; Growing shareholder value through innovation and superior performance; Leading with courage; Serving with pride; and Caring because there is respect for one another
About the Job
What will you do?
- The experience investigations team is responsible for delivering business insights through retrospectively looking at 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 SRA Actuarial to deliver valuable insights for the businesses that we serve (SRA and SRM)
- 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 smooth running of the experience investigations operation model
- Ensure the Experience Investigation operating model delivers business value
- Maintenance of the Experience Investigation model
- Assist with ad-hoc actuarial analyses on special projects
- Collaborate in the wider SPF 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?
Requirements:
Qualifications:
- Actuarial, Data Science or other relevant degree
- At least 3 years experience in the life insurance industry
- Good progress with actuarial exams
Experience and skills:
- Experience / knowledge of Sanlam’s life insurance products will be an advantage
- SAP HANA, R, SQL experience or knowledge of advanced analytics
- The combination of actuarial and data science experience will be an advantage
- Comfort working with and interrogating data
- 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
Personal Attributes
- Self-development - Contributing independently Interpersonal savvy - Contributing independently Nimble learning - Contributing independently Tech savvy - Contributing independently Build a successful career with us
Core Competencies
- Cultivates innovation - Contributing independently Customer focus - Contributing independently Drives results - Contributing independently Collaborates - Contributing independently Being resilient - Contributing independently Turnaround time
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: 25 September 2023 Our commitment to transformation
Method of Application
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