Pricing Data Scientist

SUMMARY:
A leading national retail organisation is seeking a Pricing Data Scientist to shape and optimise its data-driven pricing strategy. This role sits at the intersection of advanced analytics, retail economics and commercial decision-making, translating complex data into pricing insights that drive revenue growth, margin optimisation and competitive positioning.
 
Working closely with Merchandising, Sales, Marketing and Supply Chain teams, you will develop and deploy predictive and prescriptive models to support strategic pricing decisions across multiple retail formats and customer segments.

POSITION INFO:
Key Responsibilities:

• Develop and maintain predictive pricing models to optimise revenue, margin and competitiveness.
• Analyse price elasticity, customer behaviour and promotional impact to inform pricing decisions.
• Build models for demand forecasting, promotion optimisation and customer segmentation.
• Translate complex analytics into clear commercial insights and actionable recommendations.
• Conduct scenario modelling and pricing simulations to support strategic decision-making.
• Partner with cross-functional teams including merchandising, marketing, supply chain and e-commerce.
• Present pricing insights and recommendations to senior leadership and key stakeholders.
• Support the development and adoption of pricing tools and analytics capabilities across the business. 

• Degree in Data Science, Statistics, Mathematics, Computer Science, Econometrics or a related field.
• Minimum 5+ years’ experience in Data Science, advanced Analytics or Pricing Analytics.
• Strong programming experience in Python and advanced SQL.
• Experience building machine learning or predictive models.
• Experience working with large datasets and cloud or big-data platforms.
• Strong understanding of pricing methodologies, forecasting and commercial analytics.
• Ability to translate technical insights into clear business recommendations. 

• Experience within Retail, FMCG or e-Commerce environments.
• Exposure to pricing optimisation, promotion analytics or revenue management.
• Experience with tools such as Power BI, Tableau, Spark, Databricks or similar platforms.
• Exposure to A/B testing, causal inference or advanced experimentation techniques. 

• Strong analytical and problem-solving capability.
• Commercial acumen and strategic thinking.
• Ability to influence stakeholders through data-driven insights.
• Strong communication and presentation skills.
• Ability to manage multiple priorities in a fast-paced retail environment.