Product Management Leadership - AI/ML in Data, Identity, Payments, Fraud
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Assessing your cultural and operational fit
Product Management leader with experience of building multiple Data, AI/Machine Learning platforms from 0-1-N and driving adoption in Risk Management, Trust and Safety, Member Support and Growth across banking, fintech, marketplace and ecommerce companies. I enjoy and am well recognized for getting complex products delivered across organizational boundaries and with urgency while driving healthy cross functional collaboration.
University of Maryland
MS, Electrical And Computer Engineering
January 1, 2001 – January 1, 2003
National Institute of Technology, Tiruchirappalli
Bachelor of Science (BS), Electrical Engineering
January 1, 1997 – January 1, 2001
The Walt Disney Company
Director/Senior Principal Product Manager - AI/ML for Commerce, Data & Identity
October 1, 2025 – Present
The Walt Disney Company
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Spoonbill
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eBay
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Product Manager - Machine Learning/Fraud Detection and Prevention
December 1, 2016 – April 1, 2018
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Intel Corporation
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April 1, 2015 – December 1, 2016
Intel Corporation
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October 1, 2013 – April 1, 2015
Intel Corporation
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April 1, 2012 – September 1, 2013
Intel Corporation
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January 1, 2006 – March 1, 2012
CERN
Digital Design Engineer
January 1, 2004 – January 1, 2006
Geneva Area, Switzerland
Cultural Fit Analysis
The candidate has worked across diverse industries (tech, finance, entertainment) and company sizes (start-up advisor to large corporations), indicating adaptability. The progression from engineering to product management, with a strong focus on AI/ML and data, aligns with a forward-thinking, data-driven culture. However, the lack of specific project details or community involvement makes a deeper cultural fit assessment challenging.
Soft Skills & Operational Fit
The candidate's resume indicates strong leadership, cross-functional collaboration, and strategic planning skills, essential for a Director-level role. Experience in driving adoption of new technologies (AI/ML) and optimizing processes suggests a proactive and results-oriented operational fit. The descriptions highlight an ability to lead diverse teams and manage complex product lifecycles.