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Machine Learning engineer at Yelp
I am trained as a high energy physicist, and view the world in a mathematical and analytical way. I am currently applying my skills in a variety of business areas. For me, the best career is one of perpetual learning and broadening my horizons. I am in particular very interested in machine learning and big data, and I am continuously upgrading my skills. I care about issues of global climate change, and I believe it is imperative to create a more efficient and sustainable global economy. I am most certainly interested in any initiatives that support this objective. Big data can be a game changer here by streamlining supply chains, transportation, power delivery, and probably a host of things I haven't even thought about yet. My specialties are physics, mathematical model building and analysis.
McMaster University
Doctor of Philosophy (Ph.D.), physics
January 1, 2007 – January 1, 2011
University of Cambridge
Master of Science (M.Sc.), Mathematics
January 1, 2006 – January 1, 2007
Leiden University
Master of Science (M.Sc.), Physics
January 1, 2000 – January 1, 2006
Yelp
Machine Learning Engineer
December 1, 2021 – Present
Vancouver, British Columbia, Canada
Amazon
Applied Scientist
January 1, 2018 – September 1, 2021
Greater Seattle Area
Qbiz Netherlands
Machine Learning Consultant
July 1, 2016 – November 1, 2017
Amsterdam Area, Netherlands
ISVWorld
Data Scientist
June 1, 2015 – June 1, 2016
International Center for Theoretical Physics
Postdoctoral Researcher in Physics
October 1, 2013 – September 1, 2014
Trieste
McMaster University
Post-doctoral researcher in Physics
January 1, 2012 – September 1, 2013
Hamilton, Ontario
International Centre for Theoretical Physics (Trieste)
Visiting Scientist
November 1, 2011 – December 1, 2011
CERN
Intern
June 1, 2005 – August 1, 2005
Machine Learning
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a strong academic background and experience in large tech companies (Amazon, Yelp) and consulting (Qbiz), indicating adaptability to different work environments. The transition from theoretical physics research to applied data science and machine learning demonstrates a capacity for continuous learning and career evolution. However, the target role is 'Data Analyst,' which might be a step down from 'Machine Learning Engineer' or 'Applied Scientist' roles, potentially indicating a mismatch in career trajectory or expectations. The lack of specific project details makes it hard to assess alignment with collaborative or innovative cultures.
Soft Skills & Operational Fit
The candidate's resume highlights experience in building predictive models and working on complex data problems, suggesting strong analytical and problem-solving skills. The descriptions of past roles, particularly at Amazon and Qbiz, indicate an ability to deliver impactful solutions and work on project-based assignments. However, without specific project details or direct feedback, it is difficult to assess communication, teamwork, or stress handling abilities.