Senior Pricing Analyst – 29225

The Emerald Group; United Kingdom; Hybrid; GBP 45,000 - 55,000; Full time

Job summary

A leading actuarial firm in the UK seeks a Senior Pricing Analyst to use sophisticated statistical techniques for pricing actions. The ideal candidate will develop and coach analysts, create predictive models, and deliver accurate datasets. Requirements include a degree in a numerical discipline and 2+ years of relevant experience. This role offers hybrid working conditions.

Qualifications

• 2+ years experience in insurance pricing or a related analytical background.
• Proficient in using programming languages to manipulate data.
• Experience with various predictive modelling techniques.

Responsibilities

• Develop and coach Pricing Analysts.
• Approve predictive machine learning models to improve predictability.
• Deliver accurate datasets for modelling and pricing.
• Maintain pricing models and support their deployment.

Skills

Pricing models development

Statistical analysis

Programming languages (e.g., SAS)

Predictive modelling techniques

Education

Degree in a numerical discipline

Job description

The Senior Pricing Analyst will provide detailed analysis of data using sophisticated actuarial and statistical techniques that inform pricing actions to increase volume, income and profit.

• Location: Hybrid
• Type: Permanent

Key Duties (Including but not limited to):

• Develop and coach Pricing Analysts
• Develop, validate, review, and approve predictive machine learning models, exploring new techniques to improve model predictability
• Deliver up-to-date and accurate datasets for modelling, pricing, and monitoring, while exploring new data sets to enhance models
• Develop and maintain pricing models and support their deployment
• Degree level or equivalent in a numerical discipline
• 2+ years’ experience in insurance pricing or a related analytical background
• Proficient in using programming languages (e.g., SAS) to manipulate data
• Experience with predictive modelling techniques such as Logistic Regression, Log-Gamma GLMs, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Support Vector Machines, and Neural Nets