
Principal Applied Scientist at Cruise
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
"Explore. Dream. Discover." https://jerrickhoang.github.io/
Bowdoin College
Bachelor of Science - BS, Mathematics/ Computer Science
N/A – Present
Carnegie Mellon University
Master's degree, Machine Learning
N/A – Present
Cruise
Principal Applied Scientist, Tech Lead
August 1, 2021 – Present
Aurora
Staff Machine Learning Engineer
January 1, 2021 – August 1, 2021
Pittsburgh, Pennsylvania, United States
Startup
Investor
April 1, 2020 – Present
Uber Advanced Technologies Group
Senior Machine Learning Engineer
August 1, 2016 – January 1, 2021
Software Engineer II
August 1, 2015 – August 1, 2016
San Francisco Bay Area
TellApart
Software Engineer
May 1, 2015 – August 1, 2015
Software Engineering Intern
May 1, 2014 – August 1, 2014
San Bruno, CA
Software Engineer Intern
May 1, 2013 – August 1, 2013
Mountain View, California
Cultural Fit Analysis
The candidate has a strong background in large tech companies (Google, Twitter, Uber ATG, Aurora, Cruise) and a startup investor role, indicating adaptability to various organizational structures. The experience is heavily concentrated in Machine Learning, autonomous vehicles, and large-scale distributed systems. However, the target role is 'iOS Developer', which is a significant pivot from their core expertise. This lack of direct alignment with the target role suggests a low cultural fit for an iOS development team without significant upskilling or a re-evaluation of the target role.
Soft Skills & Operational Fit
The candidate's resume highlights leadership in a 100-person organization and experience in tech lead roles, suggesting strong operational and leadership capabilities. The descriptions of influencing directions and building end-to-end systems indicate strategic thinking and execution. However, specific soft skills like collaboration style or conflict resolution are not explicitly detailed.