Ageas have an exciting opportunity for a Senior Household Pricing Analyst to join the Household Pricing Team. 

The Senior Household Pricing Analyst will plan and deliver pricing related projects to deadline and quality standards. They will directly influence the future growth and profitability of the business. The role will involve the management of detailed analysis of data using sophisticated actuarial and statistical techniques in order to recommend pricing actions which increase volume and profit. 

In addition, the Senior Household Pricing Analyst will build pricing capability and core skills within the business, as well as influence the strategic direction of risk pricing team and within the wider Ageas UK Group. 

Main Responsibilities as Senior Household Pricing Analyst: 

• Management, development and coaching of Pricing Analysts. 

• Development and delivery of up to date and accurate datasets for modelling, pricing and monitoring. 

• Develop, validate, review and approve predictive and machine learning models. 

• Development and maintenance of pricing models and support for their deployment. 

• Carry out pricing analyses and prepare recommendations for senior stakeholders. 

• Carry out deployment/send instructions for rate releases and review of rates into rate engine/live environment. 

• Develop a balanced view of current and future pricing performance by combining MI, modelling results and company targets. 

• Insert responsibilities. 

• Maintenance of records to coordinate pricing decisions and implementation across teams, decision making bodies and implementation pathways.

• Execution, development and project management across all stages of the price control cycle as required. 

• Manage the use of our price positioning and competitor analysis in order to decide/recommend, as appropriate, changes to optimise Ageas’ competitive positioning and contribution per policy. 

Skills and experience you need as Senior Household Pricing Analyst: 

• 1-3 years General Insurance pricing experience. 

• Experience in insurance pricing or related analytical background. 

• Highly skilled in the use of programming language (e.g. SAS) to manipulate data. 

• Experienced in the use of a programming language (e.g. R, Matlab, Python or Octave). 

• Experience in SOME of the following predictive modelling techniques e.g. Logistic Regression, Log-Gamma GLMs, GBMs, Elastic Net GLMs, GAMs.