Can we confirm Friday delivery for account LF-2048?
2026
Customer-interaction RAG agent
A retrieval and tool-use workflow for policy and account questions, with citations, scoped lookups, and human escalation.
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I am a Data Scientist and AI Engineer with 10 years’ experience (7 in Australia), specialising in agentic applications, machine learning, language models, data-driven decision making, and AI governance. I hold a PhD in IT and Analytics and bring a combination of technical expertise and strategic vision across domains such as finance, IoT supply chain, digital health and cloud data platforms. I have led the development of privacy-preserving GenAI and ML systems, including model deployment and monitoring, applied to demand forecasting, customer segmentation, and anomaly detection, adhering to regulations and standards in data privacy (GDPR, HIPAA, APP) and responsible AI frameworks. In addition to my technical expertise, I have led agile data science teams, mentored junior engineers, and driven data solutions that deliver measurable business impact and support organisational objectives.
Three portfolio studies spanning predictive ML, retrieval, and agent workflows.
Can we confirm Friday delivery for account LF-2048?
2026
A retrieval and tool-use workflow for policy and account questions, with citations, scoped lookups, and human escalation.
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2026
A risk-ranking workflow for deciding which aged-care residents should receive review first.
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2026
A workflow for deciding which discharges should receive additional follow-up within 28 days.
Read case studySynthetic / simulated evidence All outcomes are synthetic or simulated portfolio evidence.
The methods and checks I use around a model.
Baselines, calibration, slices, and review capacity.
Retrieval, tools, citations, and escalation.
Metrics tied to the decision being supported.
Drift, missingness, failures, and response.
Clear boundaries, synthetic data, and limits.
Building useful systems with clear boundaries.
My work combines technical delivery with governance, team leadership, and clear communication of model limits.
Each case study shows the decision, method, evaluation, failure cases, and limitations.
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