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Arthur Recruitment

Senior Pricing Analyst (Technical)

London
Posted about 14 hours ago
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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.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Strong

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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.

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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
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Skills

Statistical Modeling
Machine Learning
Generalized Linear Models
Gradient Boosting Models
Python
SQL
SAS
Willis Towers Watson Radar
Willis Towers Watson Emblem
Data Analysis

Location

London, England, United Kingdom

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