Theo Vornonov

With a background in economics and finance, Theo has applied statistical and machine learning techniques to solve business problems across different domains: transport, banking, fraud detection, digital advertising, product analytics, customer acquisition, financial trading and portfolio optimisation.

Theo is an expert in all phases of the data science process, from business understanding, data acquisition, modelling through to deployment. He has worked for Atlassian using open source technology including R and Python, cloud platforms and services, through to enterprise-level analytics in public and private Australian organisations.

Key Skills and Experience
  • Data Engineering and Databases
  • Analytics and Machine Learning
  • Statistics
  • Explainable AI
  • Natural Language Processing
  • Deep Learning
Experience Relevant to Role Proposed for:

Data Scientist, Advantage Data (2016-Current)

Lead Data Scientist on Victorian Transport Accident Commission (TAC) and International Road Assessment Programme (iRAP) data science consulting projects. Activities and deliverables included substantial data and feature engineering, modelling, and visualisation using open source technologies.

Product Analyst, Atlassian (2014-2016)

Provided analytical expertise and data driven insights to allocate developer resources to maximise customer acquisition. Advised on experimental sample design for key products. Analysed randomized-control experiments to optimise customer email campaign response, user interface designs, and web site variations.

Qualifications & Training
  • Bachelor of Economics, University of Sydney, 2009 Economics/Finance Honours
Reference contact to support past performance in a project of a similar size and scale