Senior Pricing Analyst

4 weeks ago

Manchester, United Kingdom Vermelo RPO Full time

Job Title: Senior Pricing Analyst

Locations: Flexible

Role Overview

This role is for Vermelo RPO, where we are looking for a Senior Pricing Analyst to help build and shape our pricing models. You will help monitor our portfolio and deliver innovative pricing solutions within the Retail Pricing team.

You will be keeping a close eye on trading across different channels and insurance products. You will have previous experience in general insurance pricing and be familiar with the tools of the trade, such as SAS, Python, RStudio, SQL, Emblem and Radar. With your naturally inquisitive mindset, you will be well versed in the UK personal lines insurance space, and understand how the personal lines insurance market works.

As a key member of our team, you will be responsible for conducting retail price optimisation analysis/modelling, developing customer propensity and Life Time Value (LTV) models using SAS or SQL for data analysis, and creating innovative data solutions finding new ways to mine insight & present data.

Responsibilities
  1. Conduct retail price optimisation analysis/modelling.
  2. Develop customer propensity and Life Time Value (LTV) models using SAS or SQL for data analysis.
  3. Create innovative data solutions finding new ways to mine insight & present data.
  4. Build and maintain sophisticated models, prioritising a range of data science techniques.
  5. Advance the adoption of data science & statistical techniques.
  6. Communicate results to key decision makers across the business for action based on the results of pricing analysis.
  7. Collaborate with peers in pricing, underwriting, and data science.
  8. Generate insight to help make commercial decisions and strategic changes to prices to meet budget requirements.
Key Skills and Experience:
  1. Previous experience within general insurance pricing.
  2. Experience with predictive modelling techniques such as Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets, and Clustering.
  3. Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL).
  4. A good quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science, Actuarial Science).
  5. Experience of WTW's Radar software is preferred.
  6. Proficient at communicating results in a concise manner both verbally and in writing.
Behaviours:
  1. Self-motivated with a drive to learn and develop.
  2. Logical thinker with a professional and positive attitude.
  3. Passion to innovate, improve processes and challenge the norm.
  4. Personality and a sense of humour.

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