Senior Data Scientist: Big Data , AI
Tasks
- Apply MLOps version control and CI CD
- Build and validate machine learning models
- Build churn propensity uplift and next best action models
- Build dashboards and visualizations
- Conduct code reviews and contribute to standards
- Create reusable AI services components and pipelines
- Deploy machine learning models to production
- Design generative AI and agentic AI solutions
- Design recommendation and personalization models
- Engineer features for ML models
- Ensure data governance and Responsible AI compliance
- Explore and prepare data
- Frame business problems with data science
- Implement RAG patterns
- Manage delivery priorities for PI planning
- Mentor junior data scientists and graduates
- Monitor model performance and drift
- Own machine learning use cases end to end
- Partner with business and technology stakeholders
- Run experiments and A/B testing
- Set up model monitoring and drift detection
- Translate insights for non-technical audiences
- Write Python and SQL production code
Perks/Benefits
- Cell phone and data benefits
- Fibre connection discounts
- Medical aid benefits
- Retirement funds
- Risk benefits
- Staff discounts
Skills/Tech-stack
A/B | A/B Testing | AWS | Amazon SageMaker | Azure | B testing | CI/CD | Data Governance | Deep learning | Docker | Drift Detection | Flink | GCP | Git | H2O | Kafka | Kubeflow | Kubernetes | Language Models | Large Language Models | MLflow | Machine Learning | Model Drift | Model Drift Detection | Model Monitoring | NLTK | NoSQL | NumPy | POPIA | Pandas | Plotly | Power BI | Prompt engineering | PySpark | PyTorch | Python | Qlik Sense | RAG | Responsible AI | Retrieval-Augmented Generation | SQL | SciPy | Scikit-learn | Tableau | TensorFlow | XGBoost
Education
Associate Degree | Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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