Portfolio Pricing Lead
Markerstudy Ltd, City of Westminster
Portfolio Pricing Lead
Salary not available. View on company website.
Markerstudy Ltd, City of Westminster
- Full time
- Permanent
- Remote working
Posted today, 15 Jun | Get your application in now to be one of the first to apply.
Closing date: Closing date not specified
Job ref: c49999caf74b4a5888587a8adde140c4
Location ref: City of Westminster
Full Job Description
best-practice pricing methodologies, and contribute to the evolution of our pricing capability and operating model. The Pricing Portfolio Management team is responsible for innovating modelling approaches, refreshing and enhancing price optimisation methodologies, and ensuring our pricing infrastructure remains competitive, particularly within aggregator-driven markets. Key Responsibilities Lead the design, enhancement, and implementation of portfolio performance monitoring frameworks across product lines, ensuring clarity of insight and proactive issue identification. Drive pricing strategy and tactical interventions, partnering closely with the Pricing Manager and wider leadership to optimise commercial outcomes. Provide senior-level analytical oversight, ensuring pricing recommendations are robust, commercially aligned, and supportive of long-term profitability goals. Collaborate strategically with Underwriting, Technical Modelling, and Data teams to refine product design, calibrate
technical models, and strengthen risk-cost feedback loops. Act as the analytical voice across the business, managing senior stakeholder relationships and confidently communicating complex insights and pricing impacts. Coach, support, and develop junior analysts, fostering a high-performing, innovative, and curious team culture. Shape and influence the Pricing roadmap, contributing to long-term strategic planning, capability development, and continuous improvement initiatives. Key Skills and Experience Extensive experience in Personal Lines Pricing, with evidence of leading projects, influencing senior stakeholders, and owning complex analytical deliverables. Strong proficiency in predictive modelling techniques, including Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Networks, and Clustering. Advanced skills in R, Python, PySpark, SAS, or SQL. Proven ability to convert complex performance data into clear, commercially actionable recommendations.
Experience with WTW Radar and Emblem is essential. Exceptional communication skills, capable of simplifying complexity and shaping decisions at all levels. A strong quantitative academic background in Mathematics, Statistics, Engineering, Physics, Computer Science, or Actuarial Science. Behaviours Highly self-motivated, with a strong commitment to developing and mentoring others. Logical, structured thinker with a proactive and positive approach to problem-solving. Passionate about innovation, continuous improvement, and challenging established ways of working.
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