Senior Pricing Analyst (Technical)

Arthur Recruitment; Greater London; Hybrid; GBP 70,000 - 100,000; Full time

Job summary

Arthur Recruitment is seeking a Senior Pricing Analyst for a leading personal lines insurer's Home insurance team. The role centers on developing and executing models and analyses that underpin market pricing, requiring strong GLM and ML expertise.

The position is largely remote with 1–2 days in the London office per month, offering exposure to risk model updates and cross-functional collaboration.

Qualifications

• Strong knowledge of statistical modeling techniques, especially GLMs.
• Familiarity with machine learning methods, particularly GBMs.
• Demonstrated experience working with large datasets.
• Proficient in Python, SQL, SAS or similar programming languages.
• Experience with Willis Towers Watson software, including Radar and Emblem.

Responsibilities

• Contribute to planning and execution of risk model updates, improving data quality and processes.
• Collaborate with teams to understand requirements, data needs, and modeling outcomes.
• Engage with data from sourcing through to modeling and implementation in rating.
• Analyze data, interpret outputs, and communicate insights to non-technical audiences.

Skills

GLMs

Statistical modeling

Machine learning

Large datasets

Pricing analytics

Tools

Python

SQL

SAS

Radar

Emblem

Job description

I am working with a leading personal lines insurer seeking a Senior Pricing Analyst within their Home insurance team.

The successful candidate will be instrumental in developing and executing models and analyses that form the foundation of market pricing. This role requires a strong grasp of statistical modeling methods, along with expertise in advanced machine learning techniques.

Largely remote working with 1/2 days in the London office per month.

Responsibilities:

• Contribute to the planning and execution of risk model updates, continuously improving data quality and processes.
• Collaborate with teams and stakeholders to understand their requirements, data needs, and desired modeling outcomes.
• Engage with data from sourcing through to modeling and implementation in rating.
• Analyse data, interpret outputs, and effectively communicate insights to non-technical audiences.

Requirements:

• Strong knowledge of statistical modeling techniques, especially Generalized Linear Models (GLMs)
• Familiarity with machine learning methods, particularly Gradient Boosting Models (GBMs)
• Demonstrated experience working with large datasets
• Proficient in Python, SQL, SAS, or similar programming languages
• Experience with Willis Towers Watson software, including Radar and Emblem