About the position
Our client a leading player in the alcohol manufacturing and distribution sector based in Gauteng is building world-class analytics capabilities. They are seeking a talented Data Scientist to join their team on an initial contract with excellent potential for extension or permanent placement.
In this high-impact role you will design, build and productionise ML/AI solutions that optimise manufacturing processes, enhance distribution efficiency, improve demand forecasting, and unlock powerful consumer insights. You will work with modern MLOps practices, scalable pipelines and cross-functional stakeholders across the region delivering measurable value from day one.
Job Purpose:
Develop and deploy production-grade machine learning and artificial intelligence solutions that generate measurable business value across the organisation. The Data Scientist contributes to end-to-end analytics delivery, building scalable solutions in collaboration with team members and business stakeholders. This role combines solid technical skills in ML development and MLOps fundamentals with effective communication and a drive for continuous learning.
Key Responsibilities:
You will contribute to end-to-end analytics delivery by:
· Design, build and deploy production-grade machine learning and artificial intelligence solutions and products for business specific use cases.
· Design, build and deploy end-to-end machine learning pipelines from data ingestion through model training to production inference and monitoring; ensuring solutions meet enterprise standards for reliability and performance.
· Implement MLOps best practices including CI/CD automation with testing, validation, monitoring and deployment strategies.
· Implement A/B testing frameworks to validate model improvements in production environments and measure incremental business impact.
· Participate in applying team standards for code quality, maintainability and best practices to continuously improve personal and team output.
· Share knowledge and collaborate with team members on technical approaches in the data science domain.
· Develop reusable Python packages for common machine learning workflows with robust dependency management, versioning, and automated updates to ensure consistency and security across production pipelines.
· Build relationships with regional and global analytics, data and business stakeholders to facilitate cross-functional collaboration.
RequirementsRequirements: Education, Experience & Skills:
Qualifications & Experience:
· Bachelor’s Degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, Physics, or related quantitative field required.
· Master’s degree beneficial.
· 5+ years in a technical analytics or data science environment.
Must Have: Production Machine Learning & Technical Expertise:
· Proficient in Python with strong software engineering practices including unit testing, integration testing, version control, code reviews, and documentation.
· Experience deploying ML models to production with automated CI/CD pipelines, monitoring, and retraining workflows.
· Experience implementing monitoring for production ML systems including data quality checks, model performance metrics, drift detection, and alerting.
· Knowledge of containerisation and model deployment orchestration strategies.
· Experience with at least one major cloud platform (Azure strongly preferred given Databricks integration, AWS or GCP acceptable) including compute, storage, and managed services.
Must-Have: Machine Learning & Analytics:
· Strong foundation in statistical methods, machine learning algorithms and model evaluation techniques.
· Practical knowledge of model validation, cross-validation strategies, holdout test design, and A/B testing for production model evaluation.
· Understanding of data quality frameworks, schema validation, and automated testing for data pipelines.
· Familiarity with data governance principles, data lineage, and compliance requirements.
Must-Have: Project & Delivery Management:
· Ability to manage multiple concurrent projects, prioritise effectively based on business impact, and deliver results under tight timelines.
· Strong problem-solving capabilities with structured approaches to breaking down complex challenges.
Nice-to-Have (Highly Advantageous):
Given our client operates in the alcohol manufacturing and distribution space, the following are particularly relevant and will strengthen your application:
· Demonstrated experience building analytics solutions in FMCG, CPG, retail, or beverage alcohol industries with measurable business impact.
· Experience with causal inference methods (difference-in-differences, propensity score matching, synthetic controls) for measuring promotional effectiveness and marketing mix modelling.
· Experience with advanced forecasting techniques such as hierarchical forecasting or neural forecasting methods.
· Familiarity with LLMs and generative AI applications in business contexts.
· Experience building consumer segmentation, churn prediction, or customer lifetime value models.
· Certifications in cloud platforms (Azure Data Scientist Associate, AWS ML Specialty) or Databricks certifications.
· Experience working in agile environments using frameworks like Scrum or Kanban, including sprint planning, backlog grooming, and iterative delivery.
Ready to make an impact?
This is more than a contract, it’s your opportunity to shape analytics excellence in a major South African industry while building a long-term relationship with a forward-thinking employer.
Desired Skills:
- Python
- MLOps
- Machine Learning
- Model Deployment
- CI/CD Pipelines
- Azure
- A/B Testing
Desired Qualification Level:
- Degree
About The Employer:
