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Data Scientist at the Government of Ontario
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
Master of Engineering (M.Eng.)
January 1, 2015 – January 1, 2017
Carleton University
Bachelor of Engineering (B.Eng.)
January 1, 2005 – January 1, 2009
Children, Community and Social Services | Services à l’enfance et Services sociaux et communautaires
Data Scientist
June 1, 2024 – Present
Toronto, Ontario, Canada · Hybrid
Ontario Ministry of the Attorney General
Senior Methodologist
October 1, 2019 – May 1, 2024
Toronto, Canada Area
Ontario Ministry of Indigenous Affairs
Senior Data and Information Analyst
November 1, 2017 – October 1, 2019
Toronto, Canada Area
Wondereur Inc
Head of AI
May 1, 2017 – December 1, 2017
Toronto, Canada Area
University of Toronto
Research Assistant - Machine Learning
May 1, 2016 – December 1, 2016
CH2M
Environmental Engineer
January 1, 2012 – January 1, 2015
Toronto, Canada Area
Aurora Geosciences Ltd.
Geoscience Technician
April 1, 2010 – December 1, 2011
Summit Reforestation & Forest Management LTD.
Silviculture
April 1, 2007 – September 1, 2010
Smithers, BC
Cultural Fit Analysis
The candidate has a diverse professional background spanning environmental engineering, geoscience, and data science across government and private sectors. This breadth suggests an ability to adapt to various organizational cultures and problem domains. The progression from engineering to data science roles indicates a continuous learning mindset. The target role of Data Analyst aligns well with the candidate's recent experience in data-centric roles.
Soft Skills & Operational Fit
The candidate's resume highlights roles requiring analytical rigor and project management (e.g., Environmental Engineer, Senior Methodologist). While direct soft skill assessments are not available, the progression into senior roles suggests capabilities in problem-solving and potentially leadership. The diverse work history indicates adaptability to different operational environments.