Lead Pricing Optimisation - Home

The Lead Pricing Optimisation role at Policy Expert involves developing best-practice pricing strategies, driving updates to our optimisation frameworks, and overseeing the deployment of predictive models. You'll be responsible for shaping the pricing landscape and collaborating with various teams to ensure our pricing systems stay competitive in the market.

To qualify for the Lead Pricing Optimisation position at Policy Expert, candidates should possess a minimum of 8 years of experience in pricing roles, a strong understanding of retail price optimisation, and experience with predictive modeling. Proficiency in SQL, Python, and machine learning frameworks are preferable for this role.

The Lead Pricing Optimisation role is key to Policy Expert’s success by ensuring our pricing strategies are competitive and data-informed. By leveraging data from various sources and refining our pricing algorithms, you'll help maintain our reputation as the top-rated home insurance provider in the UK.

As a Lead Pricing Optimisation at Policy Expert, you'll enjoy a range of benefits including a generous pension scheme, private medical and dental insurance, a learning budget, enhanced family leave, and access to exclusive London events—all within a flexible 50/50 hybrid work model.

Policy Expert prides itself on being an equal opportunity employer. They actively foster a diverse and inclusive environment by treating all applications equally, focusing on skills and experience, and providing accommodations as necessary during the interview process to ensure all candidates have a fair opportunity to succeed.

When answering this question, highlight specific projects where you developed predictive models for pricing. Discuss your methodology, the tools you used, and the outcomes of your models, emphasizing your analytical skills and how you've utilized data to drive pricing strategies.

Emphasize your systematic approach to data analysis. Discuss how you collect, clean, and interpret large data sets, your familiarity with statistical methods, and your ability to derive actionable insights that will inform pricing decisions.

Focus on techniques such as elasticity analysis, competitive benchmarking, and customer segmentation. Explain how you would blend quantitative analysis with market trends to form a robust pricing strategy aligned with Policy Expert's goals.

Speak to your leadership style and how you plan to motivate the team. Discuss your experience with team building, setting clear objectives, and how you foster a collaborative environment to encourage innovation and efficient workflow.

Share a particular challenge you faced in price optimisation and how you addressed it. This could involve market unpredictability or data discrepancies. Emphasize your problem-solving skills and adaptability.

Provide a clear example of a pricing strategy you have developed and executed. Detail the process, results, and lessons learned, showcasing how your strategic thinking directly contributed to business success.

Discuss your hands-on experience with SQL, including specific queries you've constructed for pricing analysis. Mention any machine learning projects if applicable, demonstrating your understanding of how they can enhance pricing models.

Explain how understanding customer behavior is critical for pricing decisions. Talk about methods you've used to assess customer preferences and how those insights shaped your pricing strategies.

Emphasize your commitment to continuous learning. Mention relevant industry publications, forums, or professional networks you engage with to keep abreast of market changes and pricing innovations.

Discuss any specific tools or software you have used for pricing analytics and monitoring, such as WTW RADAR or others. Talk about your approach to regularly reviewing and tweaking models based on real-time data.