Amin Venjara

Parsippany, NJ, United States of America

Amin Venjara

Graduated from:
  • University of Pennsylvania (USA)
  • Princeton University (USA)
  • University of California, Berkeley (USA)
USPTO Granted Patents = 3 

Average Co-Inventor Count = 8.1

ph-index = 1

Forward Citations = 11(Granted Patents)


Company Filing History:


Years Active: 2024-2025

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3 patents (USPTO):Explore Patents

Amin Venjara: Architect of the Intelligent Enterprise


Amin Venjara didn’t merely step into the role of Chief Data Officer at ADP; he was engineered for it. With a career forged at the intersection of strategy, technology, and ethics, Venjara now stewards one of the most expansive private-sector data ecosystems in the United States. Under his leadership, ADP’s data assets, representing nearly one in five American workers, are protected with rigor and translated into actionable intelligence that drives value for customers and partners alike.


At ADP, he leads cross-functional teams responsible for the company’s enterprise AI/ML platforms, data governance, product innovation, and customer success. He has also taken on P&L responsibility for ADP’s Data Products business, a unit at the frontier of the data economy. His leadership philosophy is straightforward: build customer-obsessed teams and infuse them with a culture of innovation and operational excellence.


Before this, Venjara played pivotal roles across ADP’s growth story, from GM and VP of Product for Data Products to driving the acquisition of Global Cash Card as DVP of Strategy for Compliance Solutions. His earlier decade was a crucible of experience in the startup world and the Boston Consulting Group, shaping his instinct for scalable innovation.


A polymath at heart, Venjara holds a Master's in Data Science from UC Berkeley, an MA from Princeton, and dual degrees in engineering and business from the University of Pennsylvania’s Jerome Fisher M&T Program. His insights have graced the pages of Harvard Business Review, Fortune, and HR Executive, where he continues to explore how data and machine learning will define the future of work.

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