When it comes to building data and AI platforms at scale, few companies work at the scale and speed of personal finance application Intuit CreditKarma.

Vishnu Ram, VP of Data Science & Engineering at CreditKarma, joins us to walk through how his team designed and implemented their modern data and AI platform to power 35B financial predictions daily for over 120 million members.
  • Technologies, processes, and team structure required
  • How to build a data, ML, and AI function from scratch
  • What role data observability in this equation
Vishnu Ram
Vice President, Data Science and Engineering, Credit Karma
As VP of Engineering at Credit Karma, Vishnu has been instrumental in building and scaling Credit Karma’s machine learning infrastructure, powering personalized recommendations at scale, in pursuit of helping its 136 million members make financial progress. Having been with Credit Karma for nine years, Vishnu has led development strategy and implementation of the company’s deep-learning based system comprised of an internally built machine learning platform that helps Credit Karma transform and manage data at scale. Today, Vishnu oversees Credit Karma’s Core engineering organization, responsible for helping the Credit Karma product reach a more cohesive, personalized and intelligent state, by leveraging GenAI. Prior to joining Credit Karma, Vishnu held CTO roles at Nykaa and Games24x7.
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