Data Scientist

Recruiter:

Network Recruitment

Job Ref:

NFP016592/ZG

Date posted:

Thursday, February 12, 2026

Location:

Cape Town, South Africa

Salary:

Annually

SUMMARY:
We are seeking a highly experienced Data Scientist to lead advanced analytics, forecasting, and commercial optimisation initiatives across retail, manufacturing, and digital environments. This role is suited to a strategic thinker who combines deep statistical expertise with strong commercial acumen, and is capable of building scalable models that directly drive revenue, efficiency, and decision-making.

POSITION INFO:
The successful candidate will work across forecasting, pricing, segmentation, customer analytics, automation, and optimisation projects, partnering with senior stakeholders to deliver measurable business impact.

Key Responsibilities:

Advanced Analytics & Modelling:
- Design and deploy statistical and machine learning models
- Build predictive, segmentation, and optimisation models
- Develop A/B testing frameworks and experimental design
Demand Planning & Forecasting:
- Lead forecasting and allocation system design
- Improve forecast accuracy and inventory planning
- Develop safety stock and demand optimisation models
Commercial & Strategic Analytics:
- Deliver pricing, product affinity, and optimisation models
- Support the commercial strategy with advanced analytics
Automation & Data Infrastructure:
- Automate reporting, analytics pipelines, and data workflows
- Build scalable, reproducible analytics frameworks
Stakeholder Engagement:
- Translate analytics into business strategy
- Partner with senior stakeholders across the business

Job Experience and Skills Required:

Education:
- Degree in Maths, Actuarial Sciences, Statistics, Data Analytics, Computer Science, Finance, or a related field
Experience:
- 3+ years’ experience in data science, statistical modelling, forecasting, and analytics
- Demand forecasting and planning systems
- Time-series analysis and predictive modelling
Core Skills:
- Strong SQL skills (queries, joins, validation, and reconciliations)
- Data cleansing, transformation, and visualization

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