Senior Data Scientist (Ref: 197580)

Our client operates a diverse retail portfolio spanning apparel, accessories and large-format department stores. The organisation focuses on optimising assortment complexity, supply chain responsiveness and customer experience across high-traffic channels. Analysts and data scientists drive pricing, merchandising and inventory decisions through robust analytics and scalable data platforms.

The Senior Data Scientist will lead analytics programmes that directly improve inventory efficiency, pricing precision and customer engagement. This role owns end-to-end model development—from problem definition and feature engineering to deployment and monitoring—and partners with merchandising, planning and product teams to translate models into measurable commercial outcomes. Success will be measured by reduced stock waste, improved sell-through rates and demonstrable uplift in personalised customer interactions.

• Drive the creation of predictive models for demand forecasting, price optimisation and personalised recommendations.
• Define analytical approaches that map to commercial objectives and select appropriate modelling frameworks.
• Develop reproducible data pipelines, version-controlled model artefacts and automated deployment workflows.
• Design and analyse A/B tests and holdout experiments to quantify business impact and iterate on solutions.
• Partner with merchandising, planning and product teams to prioritise initiatives and embed analytical solutions into operational processes.
• Present findings and recommended actions to senior stakeholders, translating technical details into business implications.
• Implement model governance including monitoring, validation and performance reporting to ensure production reliability.

• Minimum 5+ years of applied data science experience, with a preference for background in retail or consumer sectors.
• Track record of deploying machine learning models to production and maintaining them at scale.
• Advanced proficiency in Python, SQL and experience with data engineering frameworks or cloud platforms (e.g., Airflow, Spark, AWS/GCP).
• Practical expertise in time series forecasting, recommendation systems or pricing algorithms.
• Experience designing experiments and applying causal inference methods to measure impact.
• Strong stakeholder management and communication skills, with experience presenting to executive audiences.
• Bachelor's or higher in a quantitative field or equivalent practical experience.

• Competitive salary aligned to senior-level market rates and performance incentives.
• Structured professional development including training budgets and access to industry conferences.
• Meaningful project ownership with clear performance metrics and cross-functional visibility.
• Flexible hybrid working arrangements and a supportive approach to work-life balance.
• Comprehensive benefits package covering health, wellbeing and retirement planning.

This position Offers a strategic platform to influence commercial decisions across multiple retail formats. Candidates With demonstrable experience in forecasting, personalisation or price optimisation will be prioritised. The role requires an analytical leader who can balance technical ownership with stakeholder influence to deliver measurable business improvements.