Head of Pricing Analytics

Role Overview

The Head of Pricing Analytics is responsible for developing the data, analytical capabilities, and decision-support tools that underpin the organisation’s pricing strategy. The role manages pricing-related data sources, builds analytical models, and provides insights that enable the business to optimise pricing decisions across products, channels, and customers.

Key Responsibilities

Pricing Data Management

• Manage and maintain the data infrastructure supporting pricing analysis, ensuring accuracy, consistency, and accessibility of pricing-related data.
• Develop and maintain datasets covering sales transactions, pricing levels, customer behaviour, cost structures, and competitive pricing.
• Utilise tools such as SQL and data management platforms to extract, transform, and structure data for analysis.
• Work with IT and data teams to ensure pricing data is integrated effectively across systems.

Pricing Analytics & Insights

• Develop analytical frameworks to assess price performance, margin delivery, and pricing effectiveness across products, channels, and customer segments.
• Provide regular insights on price realisation, discounting behaviour, customer profitability, and margin drivers.
• Support pricing teams with data-driven analysis that informs pricing decisions, negotiations, and strategic initiatives.
• Identify trends and opportunities within pricing data to improve commercial outcomes.

Pricing Models & Decision Tools

• Design and build analytical models and decision-support tools that enable the pricing team to evaluate pricing scenarios and strategies.
• Develop models that assess price elasticity, margin impact, and customer response to pricing changes and ultimately drive pricing recommendations.
• Create scalable tools that allow pricing teams and commercial stakeholders to make informed pricing decisions quickly and consistently.
• Support the development of pricing simulations to evaluate potential pricing adjustments and strategic initiatives.

Price Optimisation & Advanced Analytics

• Explore and implement price optimisation approaches using advanced analytical methods and technologies.
• Leverage latest analytical tools, machine learning techniques, and data science methodologies to enhance pricing decision-making.
• Identify opportunities to improve pricing outcomes through data-driven experimentation and optimisation.
• Stay up to date with developments in pricing analytics, artificial intelligence, and optimisation technologies.

Reporting & Performance Monitoring

• Develop and maintain pricing dashboards and reporting frameworks to provide visibility on pricing performance.
• Deliver clear reporting on key metrics including margin performance, price realisation, discount trends, and promotional effectiveness.
• Provide analytical support for commercial reviews, pricing strategy discussions, and business planning.

Collaboration with Pricing Teams

• Partner with the Category Pricing Business Partner to support category-level pricing analysis and cost pass-through evaluation.
• Work with the Channel Pricing Manager to analyse pricing performance across routes to market.
• Support the Network Pricing Business Partner with insights on customer pricing behaviour, discounting patterns, and profitability.
• Translate analytical findings into practical recommendations that support pricing teams in their decision-making.

About You

Skills & Experience

• Experience in pricing analytics, commercial analytics, data science, or business intelligence roles.
• Strong technical capability in data analysis and modelling, including experience with SQL and analytical tools.
• Experience building data models, dashboards, and analytical frameworks.
• Understanding of pricing strategies, commercial performance metrics, and margin analysis.
• Ability to translate complex analytical insights into clear business recommendations.
• Experience with tools such as Python, R, Power BI, Tableau, Alteryx or similar analytics platforms is advantageous.

Key Competencies

• Strong analytical and problem-solving capability
• Data-driven decision making
• Commercial awareness
• Technical and data management skills
• Communication and storytelling with data
• Cross-functional collaboration

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