Innovation Actuarial Analyst Trainee

4 weeks ago

London, United Kingdom SCOR Full time

Joining as an Innovation Actuarial Analyst Trainee, you’ll be part of a pioneering Innovation Team dedicated to enhancing processes and systems. This role offers exposure to extensive data projects encompassing data analytics, programming, and machine learning. Collaborating across SCOR, you’ll contribute to acquiring new business and fostering market initiatives for profitability. Additionally, you’ll have the chance to collaborate with the global SCOR team, expanding your professional network and experience.

Joining in this role you will help support the Innovation team deliver its strategic plan, where we aim to ‘Intentionally improving outcomes for customers, for clients, the market and SCOR’. You will help us deliver on all three of our strategic pillars:

Understanding distribution – helping to reduce misrepresentation across the market and improve the quality of distribution through working with our clients. 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.

Utilising new data technique and technology will underpin our ability to deliver our strategic plan and this role is key to helping us achieve this. 


Developing and enhancing predictive models

Building new, and enhancing existing, predictive models will be a core part of the role. This could include:

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.

Large data handling and exploration

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.

Research and development

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.

Pricing and risk control

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

Client and stakeholder management 

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

Required experience & competencies

Essential:

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.

Desirable:

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

Personal Competencies

Excellent analytical skills Self-motivation Customer focus Team work Attention to detail  Excellent communication and interpersonal skills

Required Education 

Undergraduate Degree in Actuarial Science, Mathematics, Data Science or other numerical degree, or equivalent qualifications 

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