Data/Applied Scientist | PhD | Gen AI, Agents Systems, ML
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
University of Melbourne
PhD, Computer Science
January 1, 2009 – January 1, 2012
Lomonosov Moscow State University (MSU)
MS, Computer Science
January 1, 2003 – January 1, 2005
Tashkent University of Information Technologies
BS, Telecommunications
January 1, 1999 – January 1, 2003
Commonwealth Bank
Principal Data Scientist
October 1, 2025 – Present
Brisbane, QLD · Hybrid
Amazon
Senior Applied Scientist
July 1, 2022 – September 1, 2025
Amazon
Applied Scientist (Machine Learning)
September 1, 2021 – July 1, 2022
University of Adelaide
Lecturer
February 1, 2021 – September 1, 2021
Adelaide, South Australia, Australia
Amazon
Applied Scientist (Machine Learning)
October 1, 2017 – January 1, 2021
Greater Seattle Area
Walter and Eliza Hall Institute of Medical Research
Postdoctoral Researcher
February 1, 2013 – September 1, 2017
Melbourne, Australia
Walter and Eliza Hall Institute of Medical Research
Research Assistant
October 1, 2012 – February 1, 2013
Melbourne, Australia
Samsung Electronics
Software Engineer
October 1, 2005 – February 1, 2009
Suwon, Gyeonggi-do, Korea
MCST
Software Engineer
May 1, 2004 – August 1, 2005
Moscow, Russian Federation
Cultural Fit Analysis
The candidate has a diverse background spanning academia (lecturer, postdoctoral researcher), large tech companies (Amazon, Samsung), and research institutions. This breadth suggests adaptability and an ability to thrive in various environments. The progression from software engineering to applied science and principal data scientist roles indicates a continuous learning mindset and ambition. The experience in GenAI/ML projects aligns with modern data-driven cultures. However, without specific project details or team interaction examples, a deeper cultural fit analysis is limited.
Soft Skills & Operational Fit
The candidate's experience as a science lead at Amazon suggests strong leadership, project management, and cross-functional collaboration skills. The description of mapping business goals to research problems and coordinating with product teams indicates a good understanding of operational workflows and business impact. However, without specific psychometric test results or interview data, a detailed assessment of stress handling, work attitude, and team collaboration is not possible.