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Rates algo trading at JP Morgan
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Scuola Internazionale Superiore di Studi Avanzati di Trieste
Doctor of Philosophy (PhD), Statistical Physics
January 1, 2010 – January 1, 2014
Università degli Studi di Bari
Laurea (Master Degree), Theoretical Physics
January 1, 2008 – January 1, 2010
Università degli Studi di Bari
Laurea (Bachelor Degree), Physics
January 1, 2005 – January 1, 2008
JPMorganChase
Rates automated trading strategies, ED
February 1, 2026 – Present
London, England, United Kingdom
JPMorganChase
Rates automated trading strategies, VP
October 1, 2020 – February 1, 2026
London, England, United Kingdom
Blockchain
Head of Data Science
November 1, 2018 – October 1, 2020
London, United Kingdom
Stratagem Technologies
Lead Machine Learning Researcher
June 1, 2017 – October 1, 2018
Stratagem Technologies
Machine Learning Researcher
October 1, 2016 – May 1, 2017
Hudson Data
Data Scientist
March 1, 2016 – September 1, 2016
New York City, Stati Uniti
Rutgers University
Postdoctoral associate
September 1, 2014 – September 1, 2016
Piscataway, NJ
SISSA
Phd Student
November 1, 2010 – July 1, 2014
Trieste, Italia
Cultural Fit Analysis
The candidate's background is heavily skewed towards quantitative finance, machine learning research, and academic physics. While these fields require strong analytical skills, the direct alignment with a 'Data Analyst' role might be an overqualification or a mismatch in terms of day-to-day responsibilities, which often involve more standard business intelligence, reporting, and less advanced model development. The diversity of projects is not explicitly detailed, making it hard to assess breadth beyond quantitative finance and research. The candidate's experience level (16 years) is very senior for a typical Data Analyst role, which might indicate a potential cultural mismatch if the role is not highly specialized or strategic.
Soft Skills & Operational Fit
The candidate's career progression into leadership and executive director roles suggests strong leadership, strategic thinking, and potentially good communication skills, although direct evidence from assessment data is missing. The academic background and research experience imply strong analytical rigor and problem-solving abilities. The transition from academic research to industry roles in finance and data science indicates adaptability and a results-oriented mindset.