Guardian Financial Services
Lead Pricing Scientist - Hybrid Working
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Guardian has a single ambition, for every family to have protection that they truly believe in. We aim to achieve that by challenging the market and offering a ‘better’ way for Financial Advisers and their clients. In line with our brand promise Life. Made Better., we plan to make life better for everyone.
You’ll be joining us at a time of growth, with lots of opportunities to increase your knowledge and further your career. You’ll be part of an innovative business, with a team of people dedicated to doing the right thing for our customers. A team where you can make a real difference and be part of a culture that encourages you to constantly challenge the norm and put our customers at the heart of every decision.
What You’ll Be Doing
As part of Guardian's Pricing & Reinsurance team, you will play a leading role in shaping pricing decisions and performance across the business. Reporting to the Head of Pricing & Reinsurance, you will combine pricing expertise, advanced analytics, machine learning and AI-enabled automation to deliver actionable insights, optimise pricing outcomes, improve profitability and customer value, and strengthen Guardian's competitive position in the UK protection market.
Working closely with colleagues across Distribution, Proposition, Operations, Data and Technology teams, you will lead the development of Guardian's pricing science capability. You will develop and enhance pricing models, deliver commercial insights, identify opportunities to improve pricing sophistication and automation, and support the evolution of next-generation pricing solutions while maintaining robust governance and controls.
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Key Responsibilities
Pricing Strategy & Delivery
- Lead the development and optimisation of pricing across Guardian's product portfolio.
- Own the end-to-end repricing process, balancing competitiveness, customer outcomes and profitable growth.
- Maintain and enhance pricing methodologies, assumptions and segmentation frameworks.
- Provide pricing recommendations that support commercial objectives and strategic priorities.
Pricing Science & Analytics
- Lead the development of pricing data science capability within the Pricing & Reinsurance team.
- Own and develop Guardian's pricing models, ensuring they remain robust, controlled and fit for purpose.
- Apply advanced analytics, machine learning and predictive modelling to improve pricing performance.
- Use internal and external data to identify pricing opportunities, improve segmentation and support growth.
Portfolio Performance & Commercial Insight
- Monitor portfolio and pricing performance, identifying trends, risks and opportunities.
- Develop insight into customer behaviour, price elasticity and market dynamics to inform pricing decisions.
- Design and maintain monitoring frameworks to track performance against expectations.
- Translate complex analysis into clear commercial recommendations for senior stakeholders.
Pricing Transformation & Automation
- Drive the automation of pricing analysis, monitoring and reporting processes.
- Lead the adoption of AI-enabled pricing capabilities and support the Pricing Transformation programme.
- Identify new data sources, modelling techniques and automation opportunities to enhance pricing sophistication.
- Partner with Data and Technology teams to build scalable pricing capabilities.
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Stakeholder Management & Governance
- Collaborate with Distribution, Proposition, Operations, Data and Technology teams to deliver pricing outcomes.
- Ensure compliance with actuarial standards, Consumer Duty requirements and internal governance frameworks.
- Maintain robust controls, documentation and oversight of pricing models, AI outputs and decision-making processes.
Knowledge, Skills & Experience
- Significant experience in pricing, data science, actuarial, analytics or a similar commercially focused role within insurance or financial services.
- Strong pricing and analytical expertise, ideally within the UK protection or life insurance market.
- Advanced modelling and programming capability, including experience with R, Python, SQL, machine learning and predictive analytics.
- Proven ability to translate complex analytical insights into commercial recommendations and pricing decisions.
- Experience developing pricing, risk, propensity or optimisation models and working with large, complex datasets.
- Strong stakeholder management and communication skills, with experience influencing senior decision-makers.
- Track record of delivering analytical solutions, automation or transformation initiatives that improve business outcomes.
- Degree-qualified in a quantitative discipline (e.g. Data Science, Statistics, Mathematics, Actuarial Science, Economics or Computer Science); actuarial qualification or equivalent professional experience would be advantageous.
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