Title:  Senior Data Scientist

We Go Places! How about you?
Immediate Superior: Chapter Lead: Data Science
Location: Sandton, Gauteng
Function: Digitial and Technollogy
Sub Function: AME Analytics Hub
Type of Contract: Permanent
Reference Number: 150798 
Closing Date: 31 January 2026

Drive the development and deployment of production-grade machine learning and artificial intelligence solutions that generate measurable business value across the organisation. The Senior Data Scientist acts as a technical leader who bridges data science innovation with operational deployment, ensuring analytics solutions are scalable, maintainable, and embedded in business processes. This role combines deep technical expertise in MLOps and production pipelines with strong stakeholder management, mentoring junior team members while delivering advanced analytics solutions.

Key responsibilities:

• • 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
  • Conduct code reviews to ensure quality, maintainability, and adherence to team standards, providing constructive feedback that develops team capabilities.
  • Mentor and coach junior data scientists in technical skills including Python programming, machine learning algorithms, MLOps best practices, and production deployment patterns.
  • 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 strong relationships with regional and global analytics leadership, data and business stakeholders and product owners to facilitate cross-functional collaboration.
  • Present complex technical concepts and model results to non-technical audiences including C-suite executives, using clear visualisations and business-focused narratives that drive decision-making.

Education and Experience: 

• Bachelors Degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, Physics, or related quantitative field required.
• Master’s degree preferred.
• 5+ years in a technical analytics or data science environment

Must have (all levels):

Production machine learning and 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.

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.

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:

• 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.

The Company’s approved Employment Equity Plan and Targets will be considered as part of the recruitment process. As an Equal Opportunities employer, we actively encourage and welcome people with various disabilities to apply. Heineken Beverages (South Africa) (Pty) Ltd) is committed to an organisational culture that recognises, appreciates and values inclusion and diversity. You must be fully eligible to live and work in South Africa to apply.