Senior Pricing Analyst (Technical)

Arthur Recruitment; Greater London; Hybrid; GBP 50,000 - 80,000; Full time

Job summary

An established industry player is seeking a Senior Pricing Analyst to join their innovative Home insurance team. This largely remote role offers the opportunity to develop and execute advanced statistical models and analyses that drive market pricing. The ideal candidate will have a strong grasp of statistical techniques and machine learning methods, alongside proficiency in programming languages like Python and SQL. This is a fantastic chance to make a significant impact in the insurance sector while enjoying the flexibility of remote work with occasional office visits in London.

Qualifications

• Strong knowledge of statistical modeling techniques and machine learning.
• Experience working with large datasets and programming languages.

Responsibilities

• Contribute to risk model updates and improve data quality.
• Collaborate with teams to understand data needs and modeling outcomes.
• Analyze data and communicate insights to non-technical audiences.

Skills

Statistical Modeling Techniques

Generalized Linear Models (GLMs)

Machine Learning Methods

Gradient Boosting Models (GBMs)

Data Analysis

Python

SQL

SAS

Tools

Willis Towers Watson Software

Radar

Emblem

Job description

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Base pay range

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Consultant at Arthur | Pricing | Actuary | Insurance

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.

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Finance

Industries

• Insurance

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