Data Scientist

About

Description

To design, build, and operationalize machine learning and optimization solutions that deliver measurable improvements in planning, execution, and service performance across warehousing and logistics. Translate high-value use cases into production-ready models with clear ROI and strong user adoption.

Responsibilities

• Frame analytical problems, define success metrics, and design robust experiments (A/B tests or quasi experimental designs)
• Build data pipelines and validated training/evaluation datasets and establish and maintain feature stores as needed
• Train, evaluate, and iterate on models (including tree based methods, time series, clustering, and deep learning when appropriate)
• Implement Machine Learning Operations practices, including experiment tracking, model registry, CI/CD, and monitoring for drift and performance degradation; automate retraining where feasible
• Collaborate with Data Engineering to deliver reliable batch and API integrations into BI platforms and operational systems
• Ensure Responsible AI practices: privacy by design (POPIA), bias and impact assessments, and comprehensive model documentation (e
• g
• , model cards)
• Communicate insights clearly through data storytelling and support stakeholders via dashboards and intuitive UX integrations (e
• g
• , Power BI)
• Comply with Information Security and POPIA requirements; enforce privacy by design throughout the machine learning lifecycle
• Maintain model cards, data lineage, validation reports, and change logs to ensure audit readiness

Qualifications

• Bachelor’s degree or equivalent experience (Statistics, Computer Science, Engineering, or related)
• Azure Machine Learning, Databricks, Machine Learning Operations; CI/CD with Azure DevOps (ADO) or GitHub; testing (pytest)
• Strong Python skills (pandas, NumPy, scikit-learn), SQL; experience at scale with time-series and tabular Machine Learning

Application instructions:

• Apply Urgently!