Greater Sydney Area
Founding engineer and Head of Engineering at a Sydney-based analytics and trading firm, with 13+ years across data science, machine learning, and platform engineering. Currently building real-time trading infrastructure for sports betting and prediction markets. Rust services on a streaming data platform, probabilistic fixture matching across exchanges, and an AI-native engineering workflow built on Claude Code and MCP. Career spans elite sports analytics for the NSW Government, enterprise data quality at Europe's largest gambling corporation, process mining consulting, and predictive analytics for international development organisations including USAID and the EU. Interested in low-latency message-driven systems, prediction markets, agentic AI workflows, and the engineering culture questions that decide whether small teams ship.
Role function: Founding engineer and Head of Engineering at a Sydney-based quantitative trading and analytics firm. Built the engineering function from zero, owning order execution, real-time pricing streams, probabilistic entity matching, and automated trading across multiple exchanges and data providers. Key skills: Engineering leadership, streaming architecture, real-time trading systems, probabilistic record matching, agentic AI workflows, hiring and technical assessment, stakeholder management, Rust, Python, Go, C#, Kafka, Redpanda, Avro, Iceberg, Trino, BigQuery, GCP, Northflank, Kubernetes, Splink, dbt, Claude Code, MCP, Linear and GitLab. Key achievements: Built engineering and infrastructure from the ground up, with Rust services running production trading volume in a core market. Consolidated streaming on Redpanda with Iceberg Topics on GCS and replaced BigQuery with Trino, cutting cost and complexity. Embedded Claude Code and MCP across the engineering workflow. Ran multi-phase hiring with bespoke anti-cheating assessment infrastructure. Industry: Quantitative trading and market analytics.
Role function: Casual academic delivering advanced technology courses to undergraduate and postgraduate students across emerging computing disciplines. Combined rigorous assessment with personalised mentoring, and kept curriculum current through active research and industry engagement. Key skills: Machine learning, Python, blockchain, cybersecurity, digital forensics, instruction, mentoring and research. Key achievements: Taught 100+ students across 10+ technical subjects, with a 98% pass rate and 20% High Distinction rate. Industry: Higher education.
Role function: Data Quality Engineer specialising in building scalable data ecosystems and governance frameworks for high-throughput environments. Key skills: Data quality, data science, statistics, machine learning, data architecture, ETL testing and optimisation, dashboard development, performance testing (data), cloud computing, stream processing, workflow orchestration, data warehousing, data governance, data lineage, data management, Agile methodologies, AWS, Kubernetes, Docker, Kafka, Airflow, Python, dbt, Redshift, PostgreSQL, CI/CD pipelines, Soda Core and OpenMetadata. Key achievements: Built scalable solutions for high-volume environments, automated data management, pioneered the company’s first data quality framework and drove cross-team collaboration for quality initiatives. Industry: Responsible gambling.
Role function: Lead Data Scientist specialising in performance analytics and machine learning engineering, delivering data-driven solutions to optimise elite athletic achievement. Key skills: Data science, machine learning, data visualisation, ETL, database management (MSSQL, MongoDB, Snowflake), cloud platforms (AWS, Azure), programming (Python, R, SQL, NOSQL, Bash), business intelligence, data governance, DevOps, mentoring and executive consultation. Key achievements: Improved ETL data retrieval times by 25%, finalist at Australian Sports Technology Awards 2023, supported Olympic success for disabled and able-bodied Australian athletes. Industry: Government, high-performance sports.
Role function: Led advanced technology courses for working professionals. Key skills: Data science, curriculum development, teaching, Python libraries (Pandas, SciPy, NumPy, Matplotlib, Seaborn, Scikit-Learn, PyTorch), project-based learning and industry-academia alignment. Key achievements: Developed and delivered comprehensive data science curriculum for University of Texas program with focus on real-world applications. Industry: Education.