Senior Manager, Pricing Analytics & Optimisation

We're ASOS, the online retailer for fashion lovers all around the world. We exist to give our customers the confidence to be whoever they want to be, and that goes for our people too. At ASOS, you're free to be your true self without judgement, and channel your creativity into a platform used by millions. We're Disability Confident Committed - let our Talent team know if you need any reasonable adjustments throughout the recruitment process.

We are looking for a forward-thinking Senior Manager, Pricing Analytics & Optimisation to help transform pricing from a largely manual, reactive process into a scalable, automated, data-led capability. This role is about building the future state of pricing across our business: one where external competitor matching and BAU pricing are increasingly automated, decisioning is grounded in robust data and clear guardrails, and human intervention is focused on high-value exceptions, strategic trade-offs, and continuous optimisation.

You will combine strong commercial judgement with modern technical and analytical capability, including SQL, Python, AI-enabled tools, and cloud-based data platforms. You will play a critical role in shaping pricing logic, automation frameworks, governance, and performance measurement, working cross-functionally with Trading, Finance, Analytics, Data Science, Product, and Engineering teams. This is a high-impact role for someone excited by the opportunity to move pricing beyond manual execution and into a more intelligent, scalable, and future-ready model.

• Pricing strategy and automation
  • Lead the evolution of pricing from manual execution toward automated, rules-based, and data-led decisioning.
  • Define pricing strategies across full-price, promotional, markdown, external matching, and BAU pricing.
  • Help shape the long-term pricing vision, ensuring pricing supports profitable growth, customer trust, price competitiveness, and brand positioning.
  • Identify which pricing decisions should be fully automated, semi-automated, or remain human-led.
  • Reduce reliance on repetitive manual intervention by creating scalable decision frameworks and operating models.
• Guardrails, decision logic and governance
  • Design and maintain pricing guardrails, thresholds, floors, ceilings, and exception logic.
  • Ensure automated pricing decisions remain aligned to margin targets, stock health, trading priorities, and customer proposition.
  • Establish clear governance for overrides, escalation routes, and exception handling.
  • Create transparent frameworks so stakeholders understand how pricing decisions are made and when intervention is appropriate.
  • Balance pace and precision, ensuring automation improves speed without weakening commercial control.
• Analytics, experimentation and optimisation
  • Use data to assess pricing performance, competitor position, customer response, price elasticity, markdown effectiveness, and commercial outcomes.
  • Build robust analyses and decision-support tools using SQL, Python, and BI platforms.
  • Develop test-and-learn approaches to validate pricing changes, automation logic, and customer response.
  • Translate complex analysis into clear recommendations for senior commercial stakeholders.
  • Move the team away from ad hoc analysis toward more repeatable, scalable insight generation.
• Data, tools and future capability
  • Partner with Analytics, Data Engineering, Product, and Data Science teams to improve pricing data, tooling, and automation infrastructure.
  • Work confidently within modern data warehouse environments such as Snowflake, BigQuery, Redshift, or similar.
  • Champion the use of AI-enabled tools to improve pricing productivity, anomaly detection, scenario analysis, workflow automation, and insight generation.
  • Help define the tooling, monitoring, and reporting needed for a more intelligent pricing engine.
  • Continuously improve pricing processes by simplifying workflows, reducing duplication, and automating low-value tasks.
• Performance monitoring and control
  • Build frameworks to monitor the effectiveness of pricing automation, including: margin impact, price competitiveness, customer response, speed of decisioning, override frequency, error rates and exception trends.
  • Identify drift, unintended consequences, or weak model outcomes early and take corrective action.
  • Ensure pricing recommendations are measurable, actionable, and tied to clear commercial KPIs.
  • Support the creation of dashboards and reporting that give leadership visibility of pricing performance and risk.
• Cross-functional leadership
  • Act as a senior partner to Trading, Finance, Buying, Merchandising, Product, Engineering, Analytics, and Data teams.
  • Influence senior stakeholders in a fast-paced, matrixed environment.
  • Bring both strategic thinking and operational grip, helping the business move from concept to execution.
  • Coach and support more junior team members, raising the analytical and commercial capability of the wider pricing function.
  • Contribute to building a modern pricing culture that values curiosity, experimentation, commercial discipline, and continuous improvement.

We believe being together in person helps us move faster, connect more deeply, and achieve more as a team. That’s why our approach to working together includes spending at least 3 days a week in the office. It’s a rhythm that speeds up decision-making, helps ASOSers learn from each other more quickly, and builds the kind of culture where people can grow, create, and succeed.

About you

• Experience
  • Significant experience in pricing, revenue optimisation or commercial analytics within ecommerce, retail, fashion, or another fast-paced consumer environment.
  • Strong track record of delivering measurable commercial impact through pricing decisions.
  • Experience improving, designing, or governing automated pricing, rules-based decision systems, or scalable pricing processes.
  • Experience operating in a highly dynamic environment with multiple stakeholders and competing priorities.
  • Strong understanding of how to balance customer competitiveness, margin, inventory productivity, and brand positioning.
• Technical and analytical capability
  • Advanced analytical capability, with the ability to move from data to action with pace and confidence.
  • Strong SQL skills and experience querying large, complex datasets directly.
  • Strong working proficiency in Python for analysis, automation, modelling, or decision-support tooling.
  • Strong capability with BI and visualisation tools such as Tableau, Looker, Power BI, or similar.
  • Good understanding of experimentation, measurement, and analytical problem-solving in a commercial setting.
  • Confidence using AI tools and a practical understanding of where AI can improve pricing effectiveness and team productivity.
• Commercial and leadership skills
  • Strong commercial judgement and comfort making recommendations in ambiguous situations.
  • Excellent communication skills, with the ability to influence both technical and non-technical stakeholders.
  • Strong systems thinking: able to design scalable solutions rather than repeatedly solve the same problem manually.
  • Highly organised, curious, and proactive, with a bias for simplification and continuous improvement.
  • Comfortable leading through influence in a matrixed organisation.

Employee sample sales 25 days paid annual leave + an extra celebration day for a special moment. Discretionary bonus scheme. Private medical care scheme. Flexible benefits allowance - which you can choose to take as extra cash, or use towards other benefits. Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role.