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AI/ML Engineer @ mabl
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
John is developing intelligent systems at mabl to improve functional testing and QA. He received his B.A. in Computer Science from Harvard University and his Ph.D. in Computer Science from Vanderbilt University. His research interests include machine learning, combinatorial optimization, intelligent agents, and coordination in multi-agent systems. At Bridj he developed and applied machine learning and AI optimization techniques to transportation modeling, prediction, and optimization for improving mass transit. His research at Vanderbilt focused on the design of intelligent pedagogical agents and machine learning techniques to model important learning behaviors, including metacognition and self-regulated learning strategies, from activity traces of student interaction in educational systems.
Vanderbilt University
Doctor of Philosophy (Ph.D.), Computer Science
January 1, 2007 – January 1, 2010
Vanderbilt University
Master of Science (M.S.), Computer Science
January 1, 2005 – January 1, 2007
Harvard University
Bachelor of Arts (B.A.), Computer Science
January 1, 1997 – January 1, 2001
mabl
AI/ML Engineer
May 1, 2017 – Present
Greater Boston Area
Bridj
Research Scientist
October 1, 2015 – May 1, 2017
Greater Boston Area
Institute for Software Integrated Systems, Vanderbilt University
Research Scientist
June 1, 2013 – October 1, 2015
Greater Nashville Area, TN
Institute for Software Integrated Systems, Vanderbilt University
Research Associate
June 1, 2010 – June 1, 2013
Greater Nashville Area, TN
Lockheed Martin Advanced Technology Center
Research Intern
May 1, 2007 – August 1, 2007
Palo Alto, CA
Lockheed Martin Advanced Technology Laboratories
Research Intern
May 1, 2006 – August 1, 2006
Cherry Hill, NJ
Institute for Software Integrated Systems, Vanderbilt University
Graduate Research Assistant
August 1, 2005 – May 1, 2010
Greater Nashville Area, TN
Cultural Fit Analysis
The candidate has a strong academic and research background, with significant experience in applying advanced analytical techniques to diverse problems (transportation, adaptive learning environments). While the technical skills are highly relevant, the career path has been heavily research-oriented. The transition to a pure 'Data Analyst' role might require an adjustment in focus from novel research to more established business intelligence and reporting, which could impact cultural fit if the role is not sufficiently challenging or analytical. The lack of projects outside of academic/research settings limits the assessment of broader industry exposure.
Soft Skills & Operational Fit
The candidate's experience in leading teams and collaborating on projects suggests strong teamwork and communication skills. Their research background implies a methodical and problem-solving approach, which is beneficial for operational fit. However, without specific psychometric test results, a definitive assessment of stress handling or work attitude is not possible.