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Engineering @ NimbleRx
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 Toronto
Doctor of Philosophy (PhD), Theoretical Computer Science
January 1, 2007 – January 1, 2013
University of Toronto
Master of Science (MSc), Computer Science
January 1, 2004 – January 1, 2006
University of Waterloo
Bachelor of Mathematics (BMath), Computer Science; Combinatorics & Optimization
January 1, 2000 – January 1, 2004
NimbleRx
Engineering
January 1, 2025 – Present
Toronto, Ontario, Canada · Hybrid
Wish
VP of Engineering
March 1, 2023 – December 1, 2024
Wish
Senior Director Of Engineering
August 1, 2018 – February 1, 2023
Wish
Head of Machine Learning
October 1, 2016 – July 1, 2018
Wish
Machine Learning Scientist
November 1, 2014 – October 1, 2016
Amazon
Research Scientist
October 1, 2012 – October 1, 2014
Seattle, Washington, USA
Thoora (Subsidiary of Rogers Ventures)
Research Intern
January 1, 2010 – January 1, 2011
Toronto, Ontario, Canada
University of Toronto
Sessional Lecturer
January 1, 2010 – January 1, 2012
Toronto, Ontario, Canada
Microsoft
Software Design Engineer Intern
January 1, 2005 – January 1, 2006
Redmond, Washington, USA
University of Waterloo
Research Assistant
January 1, 2002 – January 1, 2004
Waterloo, Ontario, Canada
Cultural Fit Analysis
The candidate has a strong background in research and leadership within large tech companies (Amazon, Wish). Their academic background is highly rigorous. However, the target role is 'Data Analyst', which is a significant shift from their senior engineering and machine learning leadership roles. While their analytical skills are likely strong, the direct alignment with a pure data analyst role, which often involves more hands-on data manipulation and reporting rather than strategic ML or engineering leadership, is not immediately clear. The lack of specific project details makes it hard to assess diversity of experience beyond their stated roles.
Soft Skills & Operational Fit
The candidate's extensive leadership and research experience suggests strong analytical, problem-solving, and strategic thinking skills. Their progression through senior engineering and machine learning roles indicates strong operational capabilities and the ability to manage complex technical initiatives. However, without specific project descriptions or detailed skill sets, it is difficult to assess communication and collaboration skills beyond what is implied by leadership roles.