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Machine Learning @ Workday
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
A product focused machine learning technology leader with solid track record of delivery.
University of Toronto
Masters of Science, Computer Science
N/A – Present
University of Waterloo
Bachelor of Computer Science, Computer Science
N/A – Present
Workday
Principal Machine Learning Engineer/Scientist
December 1, 2018 – Present
Workday
Senior/Lead Machine Learning Engineer
December 1, 2016 – December 1, 2018
Workday
Machine Learning Engineer III
November 1, 2015 – December 1, 2016
Workday
Software Development Engineer II
November 1, 2014 – November 1, 2015
Electronic Arts
Machine Learning Engineer
May 1, 2013 – July 1, 2014
Wilderness First Responder
NOLS Wilderness Medicine
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a long tenure at Workday, progressing through several roles from Software Development Engineer to Principal Machine Learning Engineer, indicating loyalty and growth within an organization. Their experience spans various advanced ML domains, suggesting adaptability and a continuous learning mindset. However, the target role of 'Data Analyst' is a significant departure from their career trajectory in Machine Learning Engineering. While their analytical skills are likely strong, the role might not fully leverage their deep ML product development and leadership experience, potentially leading to a poor cultural fit if the candidate is seeking to continue in advanced ML roles.
Soft Skills & Operational Fit
The candidate describes themselves as an 'efficient and empathetic communicator facilitating multi-organization stakeholder conversations' and a mentor for junior team members, suggesting strong leadership and collaboration skills. Their experience in leading end-to-end product development implies strong project management and problem-solving abilities. However, the target role of 'Data Analyst' is a significant mismatch with their extensive Machine Learning Engineering background, which may lead to overqualification or misalignment with day-to-day responsibilities.