• Confidential Computing

• Machine Learning

• Valuation of Financial Derivatives

• Investment Portfolio Optimisation

• Mathematical Modelling of Stored Grain Microclimates 

• Solutions to Coupled PDEs

Alex is an experienced Data Scientist with over 13+ years’ of experience in Machine Learning, Mathematics, Statistics and Quantitative Analysis, developed across multiple domains, including Federal and State Government, Asset Management (Hedge Funds), Insurance, Banking (Investment and Retail), Consulting and Academia.

He runs Meetups in the areas of Data Science, R programming and Analytics Leadership & Management, which are focussed on educating, mentoring, inspiring and spurring discussion and collaboration.

He also shares his experience and knowledge through his blog https://impartiallyderivative.com/.

Alex has a dual appointment, and is also the Principal Data Scientist for a Federal Government Intelligence Agency.