* Australian Bank – Analytics Program Lead – Data Transformation Office* Australian Bank – Technical Lead - Digital Data Transformation Program* Multi-national Pharmaceutical – Data & ML Lead – Global Omnichannel Pilot* Multi-national Construction and Real Estate – Advisor - Global Customer Service Strategy

Australian Bank – Solution Engineer - Remediation Program

* Implemented Bayesian Generalized Additive Model forecasting with Python and Prophet- Forecast of demand with seasonal components, delivering forecast with 98% daily accuracy and customizable What-if Scenario enabled through finance human-in-the middle tuning* Operationalized end-to-end Lead Scoring model in Python- A 2 year transformation project to scale and deploy a Lead Scoring model we built to help improve efficiency of the local sales team. The business problem was enabling a sales team to identify the highest potential leads in the fast-moving and competitive food delivery market by gathering data and running an applicable ML model.- In order in have maximum impact, it was decided to turn this process into a production-scale solution, in collaboration with several engineers, I used Python, Airflow, Docker and Jenkins to produce a more robust product for our local Sales Analysts and Managers.- This solution was implemented with non-Analytics end-users in mind, and has led to an incremental uplift in sales efficiency of 50% and has since been recognized by global management. * Prototyped Customer Lifetime Value models in R and productionalized with Python and Kubernetes- These fundamental projects allowed Head of Growth Marketing and Head of Loyalty make informed decisions about marketing spend as well as strategic decisions and rankings.- Facilitated inferential Null Hypothesis testing experiment design, implementation and analysis for Marketing Acquisition and Retention* Using Tableau for publication of dashboards and ad-hoc analysis , grew the business end-users self service training to 10 users, supporting them through customized virtualized data model for efficient reporting consumption.* Assisted data engineering team with SSIS and migration to Google Cloud through Airflow and Kubernetes