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Machine Learning Engineer
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
I'm highly interested in machine learning and data mining.
New York University
Master of Science (M.S.), Financial engineering
January 1, 2012 – January 1, 2014
New York University
Master of Science, General Biology
January 1, 2009 – January 1, 2011
Ocean University of China
BS, Biology Science
January 1, 2005 – January 1, 2009
Snap Inc.
Machine Learning Engineer
June 1, 2023 – Present
New York City Metropolitan Area
Machine Learning Engineer
May 1, 2018 – August 1, 2022
Condé Nast
Research Engineer II
December 1, 2017 – April 1, 2018
Condé Nast
Research Engineer I
May 1, 2016 – November 1, 2017
NYU Langone Medical Center
Senior Machine Learning Programmer/ Senior Data Analyst
October 1, 2015 – May 1, 2016
NYU Langone Medical Center
Junior Machine Learning Programmer/Bioinformatic Programmer
October 1, 2014 – October 1, 2015
NYU Langone Medical Center
Research Technician
April 1, 2011 – November 1, 2011
NYU Langone Medical Center
Student Intern
August 1, 2010 – May 1, 2011
IAQF Academic Competition
November 1, 2013 – Present
• Analyzed the impact of AIG defaulting on the CDSs it wrote and the moral harzard associated with the US government making AIG’s counterparties whole. • Developed a method for hedging CDS instruments and for determing the appropriate reserves for both writers of CDS and buyer of CDS to hedge their counterparty risk. • Suggested on how regulators should establish capital requirements for these instruments.
Machine Learning
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse educational background (Biology, Financial Engineering) and experience across different sectors (medical research, publishing, tech). The transition from research to machine learning engineering roles at large tech companies suggests adaptability. However, the target role is 'Data Analyst' while most recent experience is 'Machine Learning Engineer'. While there's overlap, the specific focus and cultural expectations of a dedicated Data Analyst role might require further assessment. The project diversity is good, but the alignment with a pure Data Analyst role needs to be validated.
Soft Skills & Operational Fit
The candidate's project descriptions and experience indicate a strong analytical and problem-solving mindset. The 'IAQF Academic Competition' project demonstrates initiative and the ability to tackle complex financial problems. However, without psychometric test results or interview data, it is difficult to assess specific soft skills like teamwork, stress handling, or communication clarity in a collaborative environment.