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Physicist / Machine Learning, Modeling and Simulation Scientist
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Assessing your cultural and operational fit
Machine Learning / Data Science consultant with extensive career in physics, computer science and applied math. Main expertise: numerical modeling and high-performance computing.
Université de Montréal
Doctor of Philosophy (Ph.D.), Computational Astrophysics
January 1, 1982 – January 1, 1986
Université de Montréal
Master of Science (M.Sc.), Statistical Physics
January 1, 1980 – January 1, 1981
Université de Montréal
Bachelor of Science (B.Sc.), Physics
January 1, 1977 – January 1, 1980
Intact
Senior Machine Learning Scientist
May 1, 2016 – November 1, 2016
Greater Montreal Metropolitan Area
Playtika
Principal Data Scientist and AI Lead
January 1, 2016 – January 1, 2021
Greater Montreal Metropolitan Area
Chemical Computing Group
Director of Research and Development
January 1, 2014 – January 1, 2016
Greater Montreal Metropolitan Area
Nuance Communications
Principal Data Scientist
January 1, 2008 – January 1, 2014
Greater Montreal Metropolitan Area
Univoc
Director of Research and Development
January 1, 2005 – January 1, 2008
Montreal, Canada Area
Environment Canada
Researcher, Numerical Prediction Research Division
January 1, 2003 – January 1, 2005
Greater Montreal Metropolitan Area
SpeechWorks International
Director of Open Speech Recognition Services
January 1, 1999 – January 1, 2003
Greater Montreal Metropolitan Area
Nortel / Bell-Northern Research
Research Scientist - Applied Speech Recognition
January 1, 1993 – January 1, 1999
Greater Montreal Metropolitan Area
Oerlikon
Senior Tactical Analyst - Missile Systems Engineering
January 1, 1991 – January 1, 1993
Montreal, Canada and Orlando, Florida Area
CHUM - Centre hospitalier de l'Université de Montréal
Biomedical Physicist
January 1, 1989 – January 1, 1991
Greater Montreal Metropolitan Area
Physics Department - Université de Montréal
Physicist - Senior Research Associate
January 1, 1988 – January 1, 1989
CAE
Software Engineer
January 1, 1987 – January 1, 1988
Greater Montreal Metropolitan Area
Introduction to Data Science
Coursera
June 24, 2026 – Present
Writing Wolfram Language Functions
Wolfram U
June 24, 2026 – Present
Mathematica and Wolfram Language for Mathematics Research and Study
Wolfram U
June 24, 2026 – Present
Solving ODEs and PDEs with Wolfram Language
Wolfram U
June 24, 2026 – Present
C++ For C Programmers
Coursera
June 24, 2026 – Present
Algorithms: Design and Analysis, Part 1
Coursera
June 24, 2026 – Present
Machine Learning
Coursera
June 24, 2026 – Present
Probabilistic Graphical Models
Coursera
June 24, 2026 – Present
Computing for Data Analysis
Coursera
June 24, 2026 – Present
Using Python to Access Web Data
Coursera
June 24, 2026 – Present
Using Databases with Python
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a long and varied career, demonstrating adaptability across different company cultures and industries (academic, defense, telecom, healthcare, software, gaming, insurance). Their experience in managing teams and collaborating with data engineering suggests a team-oriented approach. However, the target role is 'Data Analyst', which might be a step down from their 'Principal Data Scientist' and 'AI Lead' roles, potentially indicating a mismatch in career trajectory or expectations for a senior individual contributor role versus a leadership position. The breadth of experience is high, but the direct alignment with a pure 'Data Analyst' role, which often focuses more on reporting and dashboarding rather than advanced model development, is moderate.
Soft Skills & Operational Fit
The candidate's extensive experience in leadership roles (Director of R&D, Principal Data Scientist, AI Lead) suggests strong leadership, project management, and mentoring skills. Their work on diverse projects, from computational astrophysics to speech recognition and gaming, indicates adaptability and a broad problem-solving mindset. The descriptions highlight a focus on developing and deploying models, analyzing complex data, and documenting findings, which aligns with operational rigor.