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Working on LLM powered experiences to reach new audiences for the Wikimedia Foundation
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Caltech
Bachelor of Science, Computer Science
January 1, 2007 – January 1, 2011
Wikimedia Foundation
Software Engineer
January 1, 2024 – Present
San Francisco Bay Area · Remote
Etsy
Staff Machine Learning Engineer
March 1, 2022 – January 1, 2024
Remote
Staff Machine Learning Engineer
March 1, 2019 – September 1, 2021
Palantir Technologies
Senior Machine Learning Engineer
June 1, 2012 – February 1, 2019
Palo Alto, California
eHarmony.com
Matching Intern
June 1, 2011 – September 1, 2011
Santa Monica, CA
Software Engineer Intern
June 1, 2010 – September 1, 2010
Santa Monica, California
California Institute of Technology
Summer Researcher
June 1, 2008 – September 1, 2009
HedgeCo Networks
Programming Intern
June 1, 2007 – September 1, 2007
Cultural Fit Analysis
The candidate has a strong background in Machine Learning Engineering and Software Engineering. While there is experience in data analysis (eHarmony, Google internships), the primary career trajectory has been in ML Engineering. The target role is 'Data Analyst', which represents a significant shift from their recent senior/staff ML engineering roles. This could indicate a potential mismatch in career aspirations or a desire to pivot. The diversity of projects and roles is high, but the alignment with the specific 'Data Analyst' target role is moderate, as their recent experience is more specialized in ML engineering.
Soft Skills & Operational Fit
The candidate's resume indicates experience in collaborative environments (e.g., working on feature store teams, NDA'd projects for clients). However, without specific project descriptions or interview data, it is difficult to assess soft skills and operational fit comprehensively. The psychometric test score is not provided, limiting assessment in this area.