Research at Anthropic. Author of Building Machine Learning Powered Applications.
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Assessing your cultural and operational fit
Research at Anthropic Previously Staff ML Engineer at Stripe, leading ML efforts on the Radar fraud team. Author of Building Machine Learning Powered Applications published by O’Reilly (bit.ly/mlpowered). Head of AI at Insight where I led over 100 applied ML projects.
Cornell University
Corporate Law, Human resources, Management control and Organizations Management
January 1, 2013 – January 1, 2014
Lycée Henri IV
Mathematics, Physics and Chemistry
January 1, 2009 – January 1, 2011
Paris-Sud University (Paris XI)
Master of Science (MSc), Artificial Intelligence
N/A – Present
CentraleSupélec
Master of Science (M.Sc.), Engineering : Major in Computer Science
N/A – Present
ESCP Business School
Master's degree, Business Administration and Management, General
N/A – Present
Anthropic
Research
May 1, 2023 – Present
San Francisco Bay Area
Stripe
Staff Machine Learning Engineer
October 1, 2021 – October 1, 2022
San Francisco Bay Area
Stripe
Senior Machine Learning Engineer
September 1, 2019 – October 1, 2021
San Francisco Bay Area
O'Reilly Media
Book Author
September 1, 2018 – January 1, 2020
Insight Data Science
Head of AI
August 1, 2018 – August 1, 2019
Insight Data Science
AI Lead, ML Engineer
June 1, 2017 – August 1, 2019
Insight Data Science
Artificial Intelligence Fellow
March 1, 2017 – May 1, 2017
Zipcar
Data Scientist
July 1, 2015 – February 1, 2017
San Francisco Bay Area
Local Motion, Inc
Data Science
March 1, 2015 – July 1, 2015
San Francisco Bay Area
CloudMoDe
Systems Engineer
June 1, 2014 – August 1, 2014
Las Vegas, Nevada Area
Fushun Coal Mine Motor Manufacturing
Factory Worker
July 1, 2012 – August 1, 2012
Milford Tribunal
Prosecutor's Assistant
June 1, 2007 – July 1, 2007
LUSIS: Deep Learning for Train Arrival Times
October 1, 2014 – Present
Deep Learning analysis for Lusis Payments. Senior year research project at Supélec. Benchmarking deep learning against existing methods such as SVMs for the prediction of train arrival times. Mission for LUSIS. Mentored by two Supélec professors, specialized in artificial intelligence and machine learning.
Cultural Fit Analysis
The candidate's career trajectory shows a strong focus on advanced AI/ML roles, including research and leadership positions. While the target role is 'Data Analyst', their background is heavily skewed towards Machine Learning Engineering and AI Research. This might indicate a potential mismatch in the day-to-day responsibilities and growth expectations for a pure Data Analyst role. However, their experience in data-driven decision-making and optimization at Zipcar and Local Motion demonstrates an understanding of business impact. The project diversity, ranging from deep learning research to practical ML applications and even a factory worker experience, suggests adaptability and a broad interest in understanding different domains.
Soft Skills & Operational Fit
The candidate's experience as a Book Author and AI Lead at Insight Data Science suggests strong communication, mentorship, and leadership skills. Their work on overhauling model release processes at Stripe indicates a focus on operational efficiency and process improvement. The diverse educational background, including business administration, suggests a broad perspective that could contribute to cross-functional collaboration.