Innovation Actuarial Analyst Trainee
SCOR
- London
- Permanent
- Full-time
- Data services - improving fairness and across of risk pricing and maximising the impact of our data capabilities.
- Bring in new customer - expanding the protection net and helping more people get protected.
- Cleaning and analysing large data sets to prepare data to build new predictive models.
- Building, training and testing new models or techniques to find most appropriate model for the required task.
- Ensure results are sensible and explainable to non-experts.
- Working and managing large underwriting data sets to help support innovation around the future of underwriting.
- Support the development of large internal databases at the centre of the firm's long-term data strategy.
- Analyse internal data to contribute to MI, profitability analysis, client management and research.
- Learn, develop and deploy the necessary techniques and tools required to analyse large datasets for commercial insight.
- Identifying and find new data sources that can deliver value to our clients, customer or internally.
- Identify appropriate external research and derive analyses from external data sets.
- Contribute to SCOR's research activities and ad-hoc opportunities as required.
- Produce accurate documentation of research work carried out and help write reports and presentations to communicate findings both internally and externally.
- Feedback data project results into internal risk control, internal pricing basis or providing commercial insights to our clients.
- Support the development of large internal databases at the centre of the firm's long term data strategy
- Learn, develop and deploy the necessary techniques and tools required to analyse large datasets for commercial insight
- Working and collaborating with internal stakeholders and our clients to ensure all stakeholders are kept informed of progress.
- Sharing results, insights and learnings across the business
- Experience of working both within a team and as a self-motivated individual
- Experience in handling and analysing large datasets and data visualisation techniques and software.
- Good working knowledge of Microsoft packages (particularly Excel/Access)
- Good knowledge or experience of coding Python and/or R or the desire to learn coding.
- Interest or knowledge of data science and machine learning technique
- Some Actuarial training (actuarial trainees or those who have given up exams will both be considered)
- Pricing experience with Knowledge of PROPHET and SAS
- Excellent analytical skills
- Self-motivation
- Customer focus
- Team work
- Attention to detail
- Excellent communication and interpersonal skills
- Undergraduate Degree in Actuarial Science, Mathematics, Data Science or other numerical degree, or equivalent qualifications