Motor Pricing - Optimisation Senior Analyst at Policy Expert

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

11 Jan, 26

Salary

0.0

Posted On

13 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Motor Insurance, Home Insurance, Pricing Principles, Statistical Modelling, Python, R, SQL, Git, Communication Skills, Stakeholder Management, Organizational Skills, Machine Learning, Data Analysis, Customer Lifetime Value, Price Sensitivity Models, Pricing Optimisation

Industry

Insurance

Description

Policy Expert – Motor Pricing - Optimisation Senior Analyst 🚀Are you ready to transform the insurance industry? Policy Expert is a forward-thinking business that loves to get things done. Leveraging proprietary technology and smart data, we offer reliable products and a wow customer experience. Having achieved rapid growth since being founded in 2011, we’ve won over 1.5 million customers in Home, Motor and Pet insurance and have been ranked the UK’s No.1-rated home insurer by Review Centre since 2013. 🏆 Hear from our team about what it's like working at Policy Expert ✨ About Pricing: We’re at the start of an exciting transformation. With bold investment in pricing, data, and technology, we’re building a new Retail Price Optimisation team to redefine how we make pricing decisions. By combining advanced analytics, machine learning, rich data, and modern cloud infrastructure, we aim to unlock faster, smarter, and fairer pricing — creating real impact for both our customers and the business. About the Price Optimisation team: We're seeking bright, ambitious individuals eager to make a meaningful impact and accelerate their growth. You'll be supported by experienced leaders in retail pricing and data science who are deeply committed to your development and success. As a lean, hands-on team, we offer a unique opportunity to take on responsibility early, drive real change, and grow alongside the business. Joining us at this early stage means you’ll help shape our innovation roadmap and team culture that’s centered around technical excellence, commercial impact, and delivering real value to our customers. Your day to day: Behavioural and Profitability Models: Develop and maintain customer lifetime value (CLTV) and price sensitivity models, to support informed pricing decisions and long-term business performance. Price Optimisation: Own and deliver pricing optimisation processes, including regular Efficient Frontier modelling and customer outcome simulations, to identify the optimal balance between volume, price, and contribution. Innovation and Advanced Analytics: Champion continuous improvement by introducing advanced analytics techniques, machine learning approaches, and modern pricing tools. Collaboration and Strategic Support: Collaborate across teams and support strategic initiatives, working closely with the Motor Risk Pricing team to align optimisation efforts and assisting the Pricing Optimisation Manager with governance materials and MI. Leadership & Mentoring: Support and mentor junior analysts, sharing knowledge and promoting best practices across the team. Who are you: We know we have high expectations, so please don’t worry if you don’t tick all the boxes, you’ll certainly learn on the job! Essential Experience in UK General Insurance (Motor and/or Home), with a solid understanding of pricing principles and regulatory governance. Commercially minded and insight-led: able to turn analysis into actionable recommendations that drive value, with a strong grasp of how price optimisation and KPIs (e.g. LTV, conversion, retention) influence business performance. Proactive with a bias for action and ownership: takes initiative to identify opportunities, drive meaningful improvements, and take accountability for outcomes. Hands-on experience with statistical modelling (e.g. GLMs, GBMs, clustering) applied to business problems Programming proficiency e.g. Python; R; SQL; Git Excellent communication and stakeholder skills, with the ability to present technical insights clearly to non-technical audiences. Strong organisational skills, with a proactive mindset and proven ability to manage multiple priorities independently in a fast-paced environment. Nice-to-have Familiarity with pricing/modelling software: e.g. Emblem, Radar, or Earnix Experience in pricing optimisation and/or applying machine learning and operations research techniques to pricing problems Experience with cloud platforms (e.g. AWS/GCP/Azure) Benefits: 📍 This role will be based in our London office in a 50/50 Hybrid mode 💸 We match your pension contributions up to 7% 🏥 Private medical & Dental cover 📚 Learning budget of £1,000 a year + Study leave (with encouragement to use it) 😁 Enhanced maternity & paternity 🚉 Travel season ticket loan 🎟️ Access to a wide selection of London O2 events and use of a Private Lounge 🌈 Employee Wellbeing Programme 🚪 Prayer room in Office What We Stand for and Next Steps “We pride ourselves on being an equal opportunity employer. We treat all applications equally and recruit based solely on an individual’s skills, knowledge, and experience. The quality and growing diversity of our team is a testament to this commitment” At Policy Expert, we are committed to fostering an inclusive and supportive environment for all candidates. If you require any reasonable adjustments during the interview process to accommodate your needs, please do not hesitate to let us know. We are dedicated to ensuring every candidate has an equal opportunity to succeed and will work with you to provide the necessary support. We aim to be in touch within 14 working days of your application – you will be notified if successful or unsuccessful. Please be encouraged to apply even if you do not meet all the requirements. Useful links: Glassdoor | Trust Pilot

Responsibilities

Develop and maintain customer lifetime value and price sensitivity models to support pricing decisions. Own and deliver pricing optimisation processes, collaborating with teams to align efforts and assist in governance materials.