We are seeking a Data Scientist passionate about turning complex commercial challenges into actionable, high-impact solutions?
We’re looking for someone to take the lead on our pricing and markdown optimisation models, refactoring and redesigning them to improve performance, scalability, and business value. You’ll work closely with data engineering and commercial teams to enhance demand forecasting, price elasticity, and markdown algorithms—building a smarter, more sustainable pricing capability that drives real financial impact.
If you thrive at the intersection of data science, optimisation, and business strategy, this role is for you.
Role Objectives
- Take ownership of existing markdown and pricing optimisation models
- Refactor, optimise, and where necessary redesign models for long-term internal ownership
- Improve performance, scalability, and interpretability of pricing algorithms
- Strengthen the link between data science, data engineering, and commercial outcomes
- Build a more robust, simplified, and sustainable markdown optimisation capability
Key Responsibilities
Pricing & Markdown Optimisation
- Maintain, analyse, and improve existing markdown and price optimisation models
- Enhance demand forecasting, elasticity modelling, and markdown effectiveness algorithms
- Translate complex commercial problems into robust data science solutions
- Continuously test, validate, and improve model performance and financial impact
Model Refactoring & Improvement
- Understand and reverse-engineer existing models
- Refactor codebases to improve structure, performance, maintainability, and explainability
- Redesign models where needed to improve accuracy, scalability, or business usability
- Introduce better modelling approaches, feature engineering, and optimisation techniques
Data Engineering Collaboration
- Work closely with data engineers to optimise pipelines feeding pricing models
- Improve data quality, feature availability, model inputs, and processing efficiency
- Support productionisation, monitoring, and automation of models
Business & Stakeholder Engagement
- Partner with pricing, planning, and commercial teams to understand real-world challenges
- Translate model outputs into actionable commercial insights
- Support adoption of models through documentation, knowledge transfer, and enablement
Core Skills & Experience
Essential
- Strong experience as a Data Scientist working on complex, production-grade models
- Solid background in statistical modelling, machine learning, and optimisation
- Strong Python and/or R, with experience in production codebases
- Experience working with large, messy, real-world commercial datasets
- Ability to understand, refactor, and improve existing model architectures
- Strong business problem-solving orientation
Highly Advantageous
- Experience in pricing, revenue optimisation, retail, merchandising, or supply chain analytics
- Exposure to demand forecasting, price elasticity, or markdown optimisation
- Strong SQL and experience working closely with modern data platforms
- Experience collaborating deeply with data engineering teams
- Background in taking models from concept, to refactor, to production
Desired Skills:
- Data
- Scientist
- Python