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AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Arizona State University
Doctor of Philosophy (Ph.D.), Biomedical Informatics
January 1, 2010 – January 1, 2016
California State University-San Bernardino
Master's degree, Computer Science
January 1, 2007 – January 1, 2010
University of Electronic Science and Technology of China
Bachelor, Telecommunications Engineering
January 1, 2003 – January 1, 2007
Log10.io
Principal Machine Learning Engineer
October 1, 2023 – Present
San Francisco Bay Area
Intel Corporation
Deep Learning Engineer
February 1, 2017 – September 1, 2023
San Francisco Bay Area
Nervana
Distributed machine learning Intern
May 1, 2016 – August 1, 2016
Palo Alto, CA
Mayo Clinic
PHD Researcher
May 1, 2012 – December 1, 2016
Scottsdale
On2 Technologies
Codec engineer Intern
June 1, 2008 – September 1, 2008
Cultural Fit Analysis
The candidate's diverse experience across academia (Mayo Clinic, Arizona State University), startups (Nervana, Log10.io), and large corporations (Intel, On2 Technologies) indicates adaptability to different organizational cultures. The research background and continuous learning (PhD, Principal ML Engineer role) suggest a growth mindset. The transition from Deep Learning Engineer to Principal Machine Learning Engineer shows career progression and ambition. While the target role is 'Data Analyst', the candidate's background is heavily skewed towards Machine Learning Engineering, which might indicate a potential mismatch in day-to-day responsibilities or a desire to pivot. However, the core data analysis skills from the PhD research are relevant.
Soft Skills & Operational Fit
The candidate's experience as a 'Tech lead' and 'PHD Researcher' suggests strong problem-solving, leadership, and project management skills. The description of training clinical experts indicates good communication and instructional abilities. The focus on optimization and efficiency aligns with operational excellence.