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Machine Learning R&D in FinTech
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Northwestern University
PhD, Industrial Engineering and Manegement Sciences
January 1, 2010 – January 1, 2015
Zhejiang University
BS/BA, Mathematics&Applied Mathematics, double major English
January 1, 2006 – January 1, 2010
Bloomberg
AI Engineer
July 1, 2024 – Present
Bloomberg
Team Lead Enterprise Quantitative R&D
May 1, 2021 – June 1, 2024
Bloomberg
Quantitative Researcher, Machine Learning
August 1, 2017 – May 1, 2021
American Express
Data Science Manager
January 1, 2016 – August 1, 2017
NYC
CNA Insurance
Predictive modeling intern
June 1, 2014 – August 1, 2014
CNA Insurance
Predictive Modeling Intern
June 1, 2013 – August 1, 2013
Chicago
Northwestern University
Research Assistant
May 1, 2013 – December 1, 2015
Evanston
SONIC Lab at Northwestern
Research Assistant
June 1, 2011 – May 1, 2013
Evanston
ING Life Insurance Company
Intern
January 1, 2010 – February 1, 2010
Hongkong
Cultural Fit Analysis
The candidate's extensive experience across various data-intensive roles (AI Engineer, Quantitative Researcher, Data Science Manager) and industries (finance, insurance, academia) demonstrates a broad skill set and adaptability. Their academic background and continuous engagement in advanced technical roles align well with a culture that values innovation and deep analytical capabilities. The transition from AI Engineer to Data Analyst might indicate a desire for a more focused analytical role, which could be a good fit if the target role involves complex data analysis and strategic insights.
Soft Skills & Operational Fit
The candidate's experience as a Team Lead and Manager suggests strong leadership, project management, and potentially good communication skills. Their research background indicates problem-solving and analytical thinking. The diverse project descriptions imply adaptability and a structured approach to complex problems.