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Software Engineering / Machine Learning Engineering at Apple
Software Engineer at Google, working on Data Science, Machine Learning and Data Processing Qualifications and experience: • PhD in Applied Mathematics and Complex Systems at the University of Tokyo (March 2012). • Bachelor and Master's degrees in Mathematics from the Swiss Federal Institute of Technology in Zurich, ETHZ (September 2008). • Work experience in image processing, risk hedging and management consulting, data analytics and software engineering. Specialties: • Deep knowledge of applied mathematics (dynamic and complex systems theory, statistics, probability theory and stochastic processes) as well as of machine learning techniques. • Working knowledge of derivatives pricing and risk hedging. • Multilingual: professional proficiency in Italian, English, German and Japanese.
The University of Tokyo
PhD, Applied Mathematics and Complex Systems
January 1, 2008 – January 1, 2012
ETH Zürich
M.Sc., Mathematics
January 1, 2007 – January 1, 2008
ETH Zürich
B.Sc., Mathematics
January 1, 2004 – January 1, 2007
Apple
Software Engineer / Machine Learning Engineer
January 1, 2019 – Present
Cupertino, California
Senior Machine Learning Engineer
January 1, 2017 – January 1, 2019
Menlo Park, California
Software Engineer
September 1, 2015 – September 1, 2017
Quantitative Analyst / Data Engineer
June 1, 2013 – August 1, 2015
CyberAgent
Data Analyst / R&D Engineer
August 1, 2012 – May 1, 2013
Tokyo, Japan
Cerego Japan
Data Analyst
March 1, 2012 – July 1, 2012
Tokyo, Tokyo, Japan
Lowendalmasai
Consultant (intern)
July 1, 2010 – November 1, 2010
KGK corp
Algorithm Development Engineer
September 1, 2009 – June 1, 2010
The University of Tokyo
PhD candidate
April 1, 2009 – March 1, 2012
Tokyo, Japan
SDI Japan
Market and Industry Research
November 1, 2008 – May 1, 2009
ETH Zurich
Research and Teaching Assistant
September 1, 2006 – August 1, 2007
Passed CFA Level 2 Exam
CFA Institute
June 24, 2026 – Present
Passed CFA Level 1 Exam
CFA Institute
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's career trajectory, moving from academic research to various data and ML roles in prominent tech companies, demonstrates adaptability and a strong drive for continuous learning. Their experience across different company cultures (startups to large corporations) and international education (Switzerland, Japan) suggests a broad perspective and potential for good cultural integration. The diversity of projects and roles aligns well with a dynamic, innovation-focused environment.
Soft Skills & Operational Fit
The candidate's extensive experience in diverse roles, including research, data analysis, and software engineering, suggests strong analytical and problem-solving skills. Their work at multiple large tech companies indicates an ability to operate within complex organizational structures. However, without specific psychometric test results or interview data, it is difficult to assess soft skills like teamwork, leadership, or stress handling directly.