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Senior Applied Scientist @ Amazon AGI
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
University of Rochester
Master's degree, Data Science
N/A – Present
McGill University
Master's Degree - Engineering
N/A – Present
Udacity
Machine Learning Engineer, Computer Science
N/A – Present
McGill University
Bachelor's Degree - Engineering
N/A – Present
Amazon
Senior Applied Scientist
April 1, 2024 – Present
Amazon
Applied Scientist II
January 1, 2023 – March 1, 2024
Amazon
Research Scientist II
December 1, 2020 – December 1, 2022
Amazon
Research Scientist I
September 1, 2018 – November 1, 2020
NYC Data Science Academy
Data Scientist
January 1, 2018 – September 1, 2018
Greater New York City Area
McGill University
Researcher – Computational Simulation (2 Years Full-Time, Master Candidate)
May 1, 2013 – May 1, 2015
Montreal, Canada Area
McGill University
Teaching Assistant – Statistical Modeling (4 Years Part-time)
January 1, 2011 – April 1, 2015
Montreal, Canada Area
Machine Learning
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's career progression at Amazon from Research Scientist I to Senior Applied Scientist demonstrates a capacity for growth and sustained performance within a large, fast-paced organization. The academic background and research roles suggest a strong inclination towards analytical rigor and continuous learning. However, the target role of 'Data Analyst' might be a step down from 'Senior Applied Scientist', potentially indicating a mismatch in career aspirations or a desire for a different type of challenge. The lack of diverse company experience outside of Amazon (post-academia) could indicate a preference for established structures, but also a potential lack of exposure to varied organizational cultures.
Soft Skills & Operational Fit
The candidate's experience as a Teaching Assistant for Statistical Modeling, including winning 'Best T.A. of the Year' multiple times, suggests strong communication, mentorship, and leadership potential. However, without specific project descriptions or behavioral assessment data, it is difficult to fully assess other soft skills like teamwork, adaptability, or conflict resolution.