Resume
Experience
Streamline (Lunio) — Data Scientist
2025 – Current
- Worked with a team to build a dynamic pricing platform for enterprise clients that surfaces revenue opportunities through demand modelling and optimisation.
- Modelled transition probabilities with a two-stage approach (hurdle classifier + gradient-boosted regressor with uncertainty estimates) and jointly developed a Markov Decision Process solver that recommends optimal prices and forecasts revenue.
- Estimated price response with causal inference and added a counterfactual data pipeline so models generalise beyond observed price points.
- Currently developing a deep Q-learning agent (PyTorch) that treats commodity-storage pricing as a sequential control problem.
- Shipped models to production on AWS with CI/CD pipelines; refactored bottlenecks to halve inference time.
- Cut monthly AWS spend by 20%+ via a dedicated cost-monitoring framework.
- Worked closely with clients to explain results, shape reward functions, and keep recommendations grounded in the business; started a paper-reading group.
Aurizn — Intern / Graduate Data Scientist
2023 – 2025
- Built LLM-based recommender systems consuming Shapley values to explain their decisions in terms non-technical stakeholders could act on.
- Worked with the team to build client-requested features and model improvements for a dynamic pricing system, including data ingestion and automated retraining that kept accuracy steady as the data shifted and cut manual upkeep.
Education
The University of Adelaide
2022 – 2024
Bachelor of Computer Science (Advanced)
Languages & tools
Proficient
PythonSQLGBTPolarsPyTorchAWSDockerGitLinux
Experienced
PySparkRust
Additional
- Scrum Master Certificate (2025)