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Applied AI @ Databricks
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Stanford University
M.S., Computer Science
January 1, 2009 – January 1, 2011
Korea Advanced Institute of Science and Technology
B.S, Computer Science
January 1, 2002 – January 1, 2009
Databricks
Staff Software Engineer
April 1, 2022 – Present
Uber
Staff Software Engineer (ML), Tech Lead Manager
March 1, 2019 – April 1, 2022
Uber
Senior Software Engineer (ML)
May 1, 2017 – February 1, 2019
Self-Employed
Translator
January 1, 2016 – January 1, 2017
Mattermark
Lead Software Engineer in Machine Learning
February 1, 2015 – February 1, 2017
Senior Software Engineer / Data Scientist
April 1, 2013 – February 1, 2015
Software Engineer
July 1, 2011 – March 1, 2013
Stanford University
Graduate Teaching Assistant
January 1, 2011 – June 1, 2011
Software Engineering Intern
June 1, 2010 – September 1, 2010
SungKyul University
Lecturer
March 1, 2009 – June 1, 2009
The Boston Consulting Group
Chief Programmer
January 1, 2009 – February 1, 2009
1-72 Armor Battalion, 2nd Infantry Division, 8th United States Army
Sergeant (Information Management Office)
January 1, 2006 – January 1, 2008
South Korea
BearingPoint
Business Analyst
June 1, 2005 – August 1, 2005
Sun Microsystems
Intern
January 1, 2005 – February 1, 2005
Skill & Expertise Endorsements
June 1, 2012 – Present
Interface design incorporating social proof and a light weight endorsement action to Profile Skills. This feature leveraged earlier work on Profile Guided Editing, and used the same guided UI to suggest skill endorsements to profile viewers. Recipients of the endorsement receive an email and on-site notification, with a landing experience that suggests they endorse people they know - creating a feel-good viral loop.
Apache DataFu
September 1, 2011 – Present
Apache DataFu is a collection of libraries for working with large-scale data in Hadoop. The project was inspired by the need for stable, well-tested libraries for data mining and statistics.
Cultural Fit Analysis
The candidate's diverse experience across major tech companies (Google, LinkedIn, Uber, Databricks) and academic roles, coupled with contributions to open-source projects (Apache DataFu), indicates adaptability and a proactive approach to learning and contribution. Their background in various domains of data and ML suggests a broad interest and ability to integrate into different team cultures. The target role of 'Data Analyst' might be a slight mismatch given their extensive senior/staff level ML engineering and leadership experience, which typically aligns with Data Scientist or ML Engineer roles. However, their foundational data analysis skills are strong.
Soft Skills & Operational Fit
The candidate's experience as a Tech Lead Manager at Uber and Staff Software Engineer at Databricks suggests strong leadership, problem-solving, and collaboration skills. Their role as a Teaching Assistant and Lecturer also indicates an ability to communicate complex technical concepts. The translation of a technical book further highlights attention to detail and deep understanding of technical subjects.