Data Scientist

SUMMARY:
We’re looking for a data scientist to join our technology team. You'll leverage cutting-edge cloud technology and work on exciting challenges that directly impact business decisions and user experiences.

POSITION INFO:
We’re looking for a data scientist to join our technology team. You'll leverage cutting-edge cloud technology and work on exciting challenges that directly impact business decisions and user experiences.
Machine learning & automation

• Design, build, test and optimise predictive models that deliver automated business intelligence
• Develop sophisticated algorithms to solve complex business challenges
• Deploy and monitor ML models in production environments with proper versioning and tracking

• Track model performance, detect drift and manage model retraining workflows
• Containerise ML applications and manage model versioning across environments
• Partner with cross-functional stakeholders to identify, scope and solve critical business problems
• Create automated reporting systems and interactive dashboards that empower data-driven decision making
• Monitor platform performance and establish key performance metrics

• Analyse diverse data sources including custom analytics, paywall metrics, and web analytics to uncover actionable business insights
• Conduct deep-dive user behaviour analysis to enhance UX and drive engagement
• Data engineering & pipeline development
• Build and maintain robust data pipelines for ingesting, processing and transforming large datasets
• Ensure data quality and implement validation checks across data workflows
• Design efficient ETL/ELT processes to support analytics and ML initiatives

• 3+ years of hands-on Python development experience
• Proven experience with big data technologies and cloud platforms Technical expertise
• Development Tools: Git version control, Jupyter Notebooks, Docker
• ML Frameworks: scikit-learn, PyTorch, TensorFlow, LightGBM, XGBoost, Pandas
• Data Engineering: SQL, DAG orchestration tools, data pipeline design, ETL/ELT processes
• Statistical Methods: Linear/logistic regression, statistical analysis techniques
• Recommendation Systems: Collaborative filtering, content-based and hybrid models
• Tree-Based Methods: Random Forests, decision trees, gradient boosting
• Advanced Techniques: Clustering algorithms, Natural Language Processing (bag-of-words, word embeddings, transformer models)
• Model Deployment: Production deployment, A/B testing, model monitoring and maintenance

• Strong SQL proficiency and database design principles
• Experience with data warehousing concepts and dimensional modelling
• Knowledge of data quality frameworks and validation processes
• Understanding of streaming vs. batch processing architectures

• Curiosity and eagerness to learn emerging technologies, platforms and methodologies
• Problem-solving approach with attention to detail and business impact
• Strong collaboration skills for working across engineering and business teams