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Ph.D. | AI Research Scientist | Manager
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
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Tel Aviv University
Doctor of Philosophy - PhD, Artificial Intelligence
January 1, 2019 – January 1, 2022
Tel Aviv University
Master’s Degree, Electrical Engineering (Computer Vision)
January 1, 2016 – January 1, 2018
Technion - Israel Institute of Technology
BSc, Electrical Engineering
January 1, 2007 – January 1, 2011
IBM
Research Scientist & Manager
July 1, 2025 – Present
Tel Aviv University
Adjunct Professor
March 1, 2025 – December 1, 2025
IBM
Research Scientist & Tech Lead
January 1, 2024 – July 1, 2025
IBM
AI Research Scientist
August 1, 2017 – December 1, 2023
Inka Robotics
Co-founder & Chief Technology Officer
January 1, 2015 – August 1, 2017
Microsoft
Computer Vision Algorithm Engineer
March 1, 2013 – February 1, 2016
Qualcomm
ASIC Engineer
May 1, 2011 – March 1, 2013
IBM
ASIC Engineer - intern
March 1, 2008 – May 1, 2011
Cultural Fit Analysis
The candidate's background is heavily skewed towards AI research, computer vision, and robotics, with significant academic and corporate research roles. While this demonstrates a strong technical foundation, the target role is 'Data Analyst'. This represents a significant pivot from their core expertise. The lack of explicit data analysis projects or roles makes the cultural fit for a pure data analyst role questionable, as their experience is more aligned with advanced AI/ML research and engineering. The diversity of roles (startup, large tech, academia) indicates adaptability, but the direct relevance to data analysis is low.
Soft Skills & Operational Fit
The candidate's experience as a manager, tech lead, and co-founder suggests strong leadership, problem-solving, and strategic thinking skills. Their academic and teaching roles indicate a capacity for knowledge transfer and continuous learning. However, without specific project details or behavioral assessment data, it is difficult to fully assess operational fit and collaboration style.