Description:
We are seeking a Data Scientist to join our team in Cape Town, onsite.
The Data Scientist will enhance, maintain, and evolve the analytical and optimisation models used to drive product assortment decisionsincluding substitution logic, leftover-stock ("carcass") balancing, and fraud-related anomaly detection.
This is a highly analytical, process-driven role suited to someone with a strong quantitative foundation, ideally with engineering or operational research training, and a mindset geared toward optimisation, efficiency, and continual improvement.
The team values sharp talentindividuals who are switched on, curious, and intellectually agile.
Key Responsibilities
Store Clustering & Assortment Optimisation
Enhance and maintain clustering models that group stores based on department-level similarities. Analyse department attributes across stores to determine optimal product allocations. Develop data-driven insights into customer needs to improve assortment effectiveness. Substitution Logic & Customer Need Modelling Build and refine models that calculate substitution scoresidentifying alternative products when preferred items are unavailable. Support decision-making about which substitutes can be routed to which stores based on demand patterns.Carcass Balancing (Leftover Stock Optimisation)
Analyse leftover stock and determine optimal redistribution strategies across stores. Build optimisation algorithms to minimise waste and maximise stock clearance efficiency.Audit, Controls & Fraud Detection
Identify outliers, unusual patterns, and potential fraud within assortment and clustering processes. Contribute to automated audit mechanisms and anomaly detection models.Model Improvement & Operational Excellence
Work with complex existing models and enhance them for improved accuracy and speed. Apply engineering thinking to streamline processes, improve throughput, and increase operational reliability. Work closely with the business to validate outputs and translate technical findings into practical actions.Cross-Functional Collaboration Partner with teams across merchandising, supply chain, planning, and analytics. Communicate insights clearly to both technical and non-technical stakeholders. Participate in experimentation, A/B testing, and continuous improvement cycles. Qualifications Bachelors or masters degree in: Engineering (Industrial, Systems, Operations, etc.) strongly preferred Operational Research Data Science, Mathematics, Statistics, or equivalent quantitative field