The Merchandise & Supply Chain data science team provides strategic and tactical inputs across the full merchandising life cycle of our retail brands and considers the entire supply chain of merchandising. Our approach to this is heavily data-driven and involves in-depth use of advanced analytical techniques like machine learning, demand forecasting, clustering, simulation and mathematical optimization. This role would have a strong focus on understanding merchandise systems and the integration of analytical outputs into these systems.
Tasks and Objectives for the role:
Understand merchandise processes and associated systems, esp. aspects of systems that drive merchandising decisions.
Ensuring appropriate statistical methodology and analytical techniques are applied to the modeling process to deliver and deploy robust and effective models.
The querying of databases to quantify merchandise performance at the most detailed level.
Working closely with merchandise & supply chain stakeholders to ensure ongoing improvements in modeling approaches and output
Critically evaluating merchandising decisions and looking for ways to drive data-driven decision making.
Effective communication and presentation of analytical results to different stakeholders.
Documentation of analytical processes and results, adhering to agreed documentation standards.
Improvement of the analytical assets (e.g. features) to ensure accuracy of models.
Contribute to the development and procurement of merchandise systems that embed advanced analytics / machine learning components.
A B degree in a numerate discipline, preferably Statistics / Mathematics / Operations Research / Industrial Engineering / Computer Science (honor’s / master’s degree preferable)
Knowledge and experience in statistical software packages (SAS / Python / R)
Experience in machine learning, clustering, demand forecasting
Knowledge of the retail industry and merchandise life cycle management would be advantageous
Understanding of supply chain principles and inventory science would be advantageous
Hands-on experience of large-scale database data interrogation and manipulation (SQL)
Experience with data mining and statistical techniques.
Excellent data interpretation skills
A customer centric approach
Good strategic and conceptual abilities
Advanced problem solving, judgment and self-management skills
Preference will be given, but not limited to, candidates from designated groups in terms of the Employment Equity Act.