Role overview:
Markerstudy Group are looking for a Pricing Analyst to join a quickly growing and developing pricing department across a range of insurance lines.
Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1.2b. The majority of business is written as the insurance pricing provider behind household names such as Co-op, Sainsbury’s, O2, Halifax, AA, Saga and Lloyds Bank to list a few.
Having acquired and successfully integrated Co-op Insurance Services in 2021 & BGLi in 2022, Markerstudy are now pursuing innovative pricing techniques, taking advantage of an award-winning insurer hosted rating platform, whilst challenging existing embedded processes.
As a Pricing Analyst, you will use your analytical skills to:
Support pricing teams in building and maintain sophisticated models via a range of data science techniques.
Monitor pricing performance via automated reporting structures.
Enable growth within Motor & Home portfolios.
Working in the retail pricing team and closely with underwriting, technical pricing & data science teams, your insight and recommendations will enable improvements to products and prices giving Markerstudy a critical advantage in the increasingly competitive insurance market.
Key Responsibilities:
Support development of advanced pricing models using a combination of traditional & data science techniques across Private Car, Commercial Vehicle & Home accounts.
Advance the adoption of data science & statistical techniques across pricing & underwriting.
Communicate results to key decision makers across the business for action based on the results of pricing analysis.
Review observed & expected performance of key accounts.
Collaborate with peers in pricing, underwriting and data science.
Facilitate automation of repeatable tasks.
Using specialist software to monitor trends and review impact of pricing proposals.
Key Skills and Experience:
Previous experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL).
A quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science, Actuarial Science).
Experience of WTW’s Radar software is preferred, but not essential.
Proficient at communicating results in a concise manner both verbally and written.
Ability to analyse, understand and interpret data from varying sources.
Behaviors:
Self-motivated with a drive to learn and develop.
Logical thinker with a professional and positive attitude.
Passion to innovate, improve processes and challenge the norm
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