Title:  Data Scientist

We Go Places! How about you?
Immediate Superior: Chapter Lead: Data Science
Location: Sandton, Gauteng
Function: Digital and Technology
Sub Function: AME Analytics Hub
Type of Contract: Permanent 
Reference Number: 155321 
Closing Date: 23/04/2026

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:

• 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 code applying team standards for quality, maintainability and best practices to continuously improve personal and team output.
• Share knowledge and collaborate with team members on technical approaches 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.

Qualifications, Experience amd skills required per job levels:

Qualifications:

• Bachelors Degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, Physics, or related quantitative field required.
• Master’s degree preferred.
• 2-5years 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.
• Stays current with machine learning and artificial intelligence industry trends and emerging technologies, evaluating applicability to business problems and sharing knowledge with the team.

Leadership competencies 

• Fosters a growth mindset and culture of continuous learning within the analytics team.
• Builds strong credibility with analytics and business stakeholders through consistent delivery of high-quality solutions.
• Promotes a culture of collaboration in the team and between teams.
• Balances multiple priorities effectively, making trade-off decisions that optimise business impact within resource constraints.
• Demonstrates composure under pressure when managing tight deadlines, changing requirements, or technical challenges.
• Learns from setbacks and incorporates lessons into improved approaches for future projects.

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.