Senior Pricing Analyst (Technical)

Arthur Recruitment; Greater London; Hybrid; GBP 65,000 - 90,000; Full time

Job summary

Arthur Recruitment is partnering with a leading personal lines insurer to appoint a Senior Pricing Analyst for their Home insurance segment. The role centers on building and executing models that underpin market pricing, leveraging GLMs and advanced machine learning techniques.

The candidate will work largely remotely with occasional London office days, and will need to translate complex data outputs for non-technical stakeholders while driving model quality and pricing strategy.

Qualifications

• 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.

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.

Skills

GLMs

Machine learning

Data analysis

Python

SQL

SAS

Tools

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