Actuarial Analyst

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

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

• Contributing significantly to SCOR's Research and Development activities, including working on mortality and morbidity trends and base tables.

• 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.

• 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

• Working and collaborating with internal stakeholders and our clients to ensure all stakeholders are kept informed of progress.

Client and stakeholder management

• Sharing results, insights and learnings across the business.

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