Principal Data Scientist – Lead Analytics & Team
The Shoprite Group of Companies · Brackenfell
Job description
About the role
The Principal Data Scientist will shape Shoprite’s data strategy, turning data into a commercial advantage while building and mentoring a high‑performing data science team. This senior position requires a blend of technical expertise, business acumen, and leadership.
Key responsibilities
- Define and drive Shoprite’s data strategy to deliver best‑in‑class analytics across the organisation.
- Lead engagements with business stakeholders to translate requirements into meaningful data models and scenarios.
- Collaborate with data and software teams to design, deploy and scale robust, fit‑for‑purpose solutions.
- Prioritise data projects, balance business and technical trade‑offs, and delegate execution responsibilities.
- Develop analytics‑focused products using machine learning, natural language processing and advanced statistical techniques.
- Manage the data science team, set modelling standards, and monitor model accuracy, integrity and robustness.
- Define data‑quality expectations and continuously track performance of data systems and models.
- Report analytical findings to senior stakeholders using compelling data visualisations.
- Evaluate emerging technologies, prototype proofs of concept, and act as a domain expert across the organisation.
Required profile
- Master’s degree in Data Science, Computer Science, Mathematics, Statistics, Engineering or a related field (essential).
- At least 8 years of experience in a lead data‑scientist role, consistently delivering complex data solutions.
- Proven ability to mentor, coach and grow data‑science talent.
Required skills
- Machine learning
- Natural language processing (NLP)
- Statistical and mathematical modelling techniques
- Decision trees and association rules
- Predictive and descriptive modelling
- Data visualization
- Big‑data environment expertise
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Published 2 weeks ago
Expires 1 month from now
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The Shoprite Group of Companies
Brackenfell
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