Building data and machine learning services to detect and mitigate fraud across all Uber’s products including Uber Rides and Uber Eats globally.- Optimized and rebuilt a data ingestion pipeline from Python and MySql into a Java service with a Cassandra datastore. These features are used in Machine learning models and rules to detect and protect against fraudulent activity. - Created Python pipelines with hive queries to disperse data from HDFS to Cassandra. This data was then used to create various dispersal and aggregation features exposed to our rules engine which caught 6k daily fraudulent drivers across Europe, the Middle East and Africa.- Worked with analysts to implement features in our Golang RPC service, blocking drivers who abused airport and uber pool trips.- Investigated and fixed MySQL rules to enable emerging products like Uber Medic to make trips to Hospitals during COVID-19.

Building financial products at Australia's largest investment bank.- Built an “Afterpay for cars” app in Typescript/React js deployed on third party car sites. Developed back end APIs and infrastructure to support the product in Node js.- Built a marketplace for vehicles site with Typescript/Angular js and Java backend. Ingested bluebook data to build an API for both our site and external dealerships around Australia. - Worked on financial services APIs in Java with Tomcat, Springboot. Migrated Java applications from on prem to AWS and Red Hat’s managed Kubernetes platform. - Developed home loan application to funnel in traffic from other Macquarie services with Angular js.

Facilitating coding and electronics workshops at the Powerhouse Museum and Sydney Observatory.

Building tools to find and fix software vulnerabilities.- Built file procurement app for fuzzing, using AWS EMR, pushing to MongoDB database.- Experimented with Dynamic Binary Instrumentation using Intel Pintool.

Managing a bespoke shoe design startup by designing UI features, running A/B tests and liasing with engineering, marketing, ops and creative.