Dana Pessach
Data AnalystAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Applied AI Leader & Research Scientist | Amazon | PhD | 15+ Yrs AI/ML, GenAI, Predictive Modeling | Responsible AI Expert
Applied AI Leader and Research Scientist with 15+ years of hands-on and leadership experience bridging cutting-edge machine learning theory with industry-scale applications. I have a proven track record of driving AI product impact at Amazon, leading advanced academic research labs (LAMBDA), and providing strategic AI consulting for high-growth startups and entrepreneurs. Currently an Applied Research Scientist at Amazon, I specialize in translating complex theoretical frameworks into production-ready models that solve high-impact business problems, ranging from predictive modeling to Generative AI (GenAI) & LLM-assisted systems and automated research workflows. My background uniquely combines deep academic expertise with over a decade of directing university AI labs (LAMBDA) and running an independent AI consulting firm focused on helping early-to-late stage startups build and scale their AI roadmaps, and extract concrete business value from unstructured data. Core Expertise: • Technical Leadership, Applied AI/ML & GenAI / LLM-Assisted Architectures • Startup AI Advisory & Cross-Functional AI Product Strategy • Algorithmic Bias Mitigation & Responsible AI
Tel Aviv University
PhD, Data Science and Artificial Intelligence
January 1, 2015 – January 1, 2021
Tel Aviv University
Master of Science (MSc), Industrial Engineering and Management
January 1, 2011 – January 1, 2013
Tel Aviv University
Bachelor of Science (BSc), Industrial Engineering and Management
January 1, 2006 – January 1, 2010
Amazon
Applied Research Scientist
December 1, 2021 – Present
retrain.ai
Senior Research Consultant - AI, Machine Learning, NLP
January 1, 2020 – January 1, 2021
Tel Aviv University
Director and Member of the Steering Committee, Lambda Artificial Intelligence Lab
February 1, 2018 – November 1, 2021
AEAI - Association of Engineers and Architects in Israel - לשכת המהנדסים
Board Member of the Israeli Data Science Society
January 1, 2017 – November 1, 2021
Tel Aviv University
Team Leader and Academic Supervisor, Technology Lab, Faculty of Engineering
October 1, 2015 – March 1, 2018
Independent AI & Data Science Advisory
Principal AI Consultant & Owner - Artificial Intelligence, GenAI, Machine Learning
October 1, 2015 – December 1, 2021
Tel Aviv University
PhD, AI and Machine Learning at the Big Data Lab
October 1, 2015 – September 1, 2021
C-B4
Head of AI/ML/DS Customer Success
December 1, 2014 – October 1, 2015
C-B4
Machine Learning Researcher and Professional Services Manager
October 1, 2012 – November 1, 2014
Tel-O-Fun
Management Consultant - Business Analysis Expert
January 1, 2010 – January 1, 2012
Tel Aviv University
Researcher, the Faculty of Engineering
January 1, 2010 – January 1, 2012
Tel Aviv University
Junior Faculty, the Faculty of Engineering
January 1, 2007 – January 1, 2012
Independent
Software Product Manager
January 1, 2007 – January 1, 2013
IT Division, The Open University of Israel
Technology Services & Support, Training and Development
January 1, 2005 – January 1, 2006
Israel Defense Forces
Team Leader
January 1, 2003 – January 1, 2005
Urban Innovation Project at Tel-Aviv Municipality
May 1, 2012 – August 1, 2012
Emergency preparedness planning. http://www.tel-aviv.gov.il/eng/residents/Pages/security.aspx?tm=1&sm=17
HuSIMS
June 1, 2011 – January 1, 2014
The HuSIMS project aims to develop a system that can improve safety and security in city centres, train stations, office buildings etc. This will be achieved by improving the effectiveness and timeliness of response to irregular situations. Respect for personal privacy is one of our key considerations. Intelligent visual sensors will be deployed in a city all along the streets. They are small and unobtrusive, and communicate wirelessly with the Monitoring and Control System (MCS) located somewhere in the city. The low optical resolution does not allow recognizing faces or people, but does allow automatic determination of scene parameters. Using advanced analysis algorithms, the MCS analyzes these parameters and makes a decision on whether that activity in the street is normal - or the recorded activity merits a second look from a controller in the control room or a security officer on the scene.
Consulting for FSM Ltd.
January 1, 2010 – January 1, 2012
http://www.haaretz.com/print-edition/features/the-cycling-equation-1.356832
Python Master - Score 100%
mypath io
June 24, 2026 – Present
Hadoop Master - Score 100%
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R Master - Score 100%
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SQL Master - Score 100%
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Google Cloud - Scientific Data Processing
Google Cloud Certified
June 24, 2026 – Present
Big data developer Master - Score 100%
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Data scientist Master - Score 100%
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Cultural Fit Analysis
The candidate's diverse experience across academia, industry (Amazon, C-B4), and consulting, coupled with leadership roles in professional societies, indicates a strong adaptability and a proactive approach to professional development. Their involvement in projects like HuSIMS and Urban Innovation suggests an interest in impactful, real-world applications of data science, aligning well with organizations seeking innovative and socially conscious contributors. The breadth of their roles, from research to customer success and management, demonstrates a versatile individual capable of thriving in various team structures and contributing to different aspects of a project lifecycle.
Soft Skills & Operational Fit
The candidate's experience as a Team Leader in the IDF, Director of an AI Lab, and various consulting roles suggests strong leadership, problem-solving, and communication skills. Their involvement in customer success and professional services indicates an ability to understand business needs and translate them into technical solutions, which is crucial for operational fit in a data-driven environment. The academic teaching experience also points to strong communication and mentorship capabilities.