Data Scientist - Contract

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.

Requirements: 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.