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Director, Machine Learning at Amazon
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Specialties: Data mining and applied machine learning
Rensselaer Polytechnic Institute
PhD, Computer Science
January 1, 2004 – January 1, 2009
Rochester Institute of Technology
Masters, Computer Science
January 1, 2001 – January 1, 2004
Bharati Vidyapeeth
Bachelors, Computer Engineering
January 1, 1995 – January 1, 1999
Savitribai Phule Pune University
BE, Computer Engineering
January 1, 1995 – January 1, 1999
De Nobili School
ICSE
January 1, 1984 – January 1, 1993
Amazon
Director, Machine Learning
October 1, 2024 – Present
Amazon
Sr. Manager, Applied Science
October 1, 2019 – October 1, 2024
Amazon
Manager, Applied Science
April 1, 2016 – September 1, 2019
Amazon
Sr. Machine Learning Scientist
May 1, 2015 – April 1, 2016
Amazon
Machine Learning Scientist
August 1, 2012 – April 1, 2015
Yahoo! Labs
Scientist
September 1, 2009 – August 1, 2012
Bangalore
Nokia Research Center, Palo Alto
Research Intern
May 1, 2008 – January 1, 2009
Microsoft Corporation
Research Intern
May 1, 2007 – August 1, 2007
Rogue Wave Software
Software Development Intern
June 1, 2002 – January 1, 2003
Persistent Systems
Member of Technical Staff
July 1, 1999 – June 1, 2001
Cultural Fit Analysis
The candidate's long tenure and progression within Amazon, a known high-performance culture, suggests a strong fit for demanding, results-oriented environments. The diverse experience across research (Yahoo! Labs, Nokia, Microsoft) and product development (Persistent Systems) indicates adaptability and a broad understanding of different organizational contexts. The academic background (PhD) also points to a strong inclination towards continuous learning and innovation. The target role of 'Director' aligns well with the candidate's experience level and career trajectory.
Soft Skills & Operational Fit
The candidate's career progression at Amazon from Scientist to Director suggests strong leadership, problem-solving, and strategic thinking abilities. The early career descriptions indicate experience in team collaboration and driving initial product development. However, without specific project details or behavioral assessment data, a detailed analysis of soft skills and operational fit is limited.