Senior Pricing Analyst (Technical)

ZipRecruiter; London; Hybrid; GBP 50,000 - 80,000; Full time

Job summary

A leading personal lines insurer is seeking a Senior Pricing Analyst to join their Home insurance team. This largely remote role offers the opportunity to develop and execute pricing models while collaborating with various teams to enhance data quality and processes. The ideal candidate will possess strong statistical modeling skills, particularly in GLMs and machine learning techniques, and will be adept at handling large datasets. This position not only allows for professional growth but also provides a chance to make a significant impact in a dynamic and supportive work environment.

Qualifications

• Strong knowledge of statistical modeling techniques and machine learning methods.
• Experience with large datasets and proficiency in Python, SQL, and SAS.

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)

Python

SQL

SAS

Data Analysis

Tools

Willis Towers Watson Software

Radar

Emblem

Job description

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