Portfolio Pricing Analyst Home

Portfolio Pricing Analyst (Portfolio Management) Home

Location: The role is hybrid and would require you to be commutable to either Manchester or London.

Role Overview

We have an exciting new role available for a Portfolio Pricing Analyst to join our team within our rapidly growing personal lines underwriting. It s the perfect opportunity for someone looking to progress with a fast-growing company and make their mark on shaping our pricing models.

As a Pricing Analyst, you will use your advanced analytical skills to:

• Monitor our portfolio and deliver innovative pricing solutions,
• Use a blend of predictive analytics and commercial acumen to distil key trends and identify pricing actions,
• Contribute to the profitability of the products by meeting loss ratio targets and protecting capacity providers financial results by balancing product volume and profitability

The Pricing portfolio management team is responsible for developing new modelling techniques and processes and building and refreshing the risk models that underpin our rates that need to operate effectively in the aggregator channels.

Key Responsibilities:

• Support the design, development and implementation of a robust and innovative performance monitoring framework
• Contribute to the continuous pricing cycle including development and deployment of tactical pricing initiatives, price optimisation proposals and price change opportunity & impact analytics.
• Work closely with the Underwriting team on risk appetite, product development and innovation supporting progression by providing performance and market analytical insight.
• Work closely with the Technical Modelling team on peril risk cost models ensuring product performance dynamics are suitably captured and fed back in technical models.
• Contribute to delivery of the pricing roadmap in line with the vision and long-term goals of the company.

Key Skills and Experience:

• Previous experience within Personal Lines Pricing is advantageous
• Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering
• Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL)
• A good quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science, Actuarial Science)
• Experience of WTW s Radar and Emblem software is preferred
• Proficient at communicating results in a concise manner both verbally and written

Behaviours:

• 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