Lead global data science & machine learning strategy and initiatives for cloud native data logging and security analyticsBuild and strengthen data science team to work on next-gen ML-based user entity behavior modeling, threat detection framework, data pipeline and and platform infra.

Managed global data science and machine learning solutions for both PayPal core and omni-channel payment product offerings including Web/app checkout, P2P transaction, in-store POS, QR code payment, cryptocurrency, credit card, debit card, ACH, and Open Banking initiativesOptimized data-driven solutions based on holistic customer lifecycle management to improve new customer acquisition and onboarding experience, existing customer engagement and customer lifetime value, increase user and transaction conversion rate with minimum risk friction.Provide tech leadership driving in-house best practice to meet internal DS/ML solution governance and compliance requirements; promoting democratization of machine learning, deep learning, explainable and responsible AI technologies.Invented innovative patent pending adverse feature identification and neutralization methodologies leveraging Explainable AI principles to boost ML performance at any desired operating range.

Managed PayPal’s global consumer risk data science solutions including PayPal’s most critical top three flagship ML solutions: Card authorization, ACH authorization, and Account takeover, to adjudicate millions of payments per day in real time while ensuring safe account, secure transaction and smooth customer experience. Pioneered and productionalized PayPal’s first large scale deep learning solution for the flagship card authorization model.Tech lead of data science track for M&A evaluation and $120 million acquisition of an e-commerce fraud detection startup to offer machine-learning-based Risk as a Service(RaaS) to online merchants.Invented innovative patent pending robust and adaptive modeling methodologies which have become PayPal’s foundational backbone architecture for all the major data science solutions since then to enhance model stability and performance while also quickly adapting any emerging behaviors and patterns.

Pioneered Hadoop cluster-based large scale machine learning and big data modeling platform and architecture with engineering teams. Built PayPal’s first large scale Neural Network solution suite scalable to training on hundred million transactions and thousands of features and productionalized for first tier of fast approval decision with lowest latency leading to significantly improved transaction conversion rate and customer experience.

Invented iterative model-based label enhancement with human guidance in the loop to develop and deploy PayPal’s first collusion fraud detection solution minimizing losses caused by coordinated buyer-seller behaviors.

Led Trust and Safety organization’s R&D initiatives to build eBay’s first suite of machine learning, text mining, and NLP solutions for both real-time and near real time risk detection from listing titles, descriptions and member communication messages, which significantly reduced fraudulent listing visibility on eBay platform and prevented large financial losses. Worked with eBay research labs (eRL) to collaborate on eBay site search engine algorithm optimization with risk impact considerations hence reducing the visibility and ranking of suspicious and risky listing content from a user’s search result to minimize potential loss and improve customer experience.