• Lead AI solutions for $4B+ Samsung ecommerce (web and native app). -- Establish partnerships, identify growth opportunities and create technical road maps. -- Build real time and batch recommendation systems for various business use cases. -- Develop AI models for customers next best actions in various funnels, driving $50M+ annual revenue. • Promote GenAI opportunities by identifying business use cases and developing MVP solutions. • Develop ML predictive models for Samsung product affinities for 200M+ customers, supporting AI driven marketing segmentations. • Lead cross-functional activities for platform (Cloudera, AWS, GCP, H2O, etc.) innovation to ensure continuous operational excellence.• Mentor and guide junior data scientists.

This extensive six-month bootcamp is designed to train professionals to transition to the AI industry. I mentor them in adopting the best technical practices and industry standards (including Python programming and statistics), navigating through intricacies of the AI industry and applying AI solutions to real world problems. The format of the mentorship includes one-on-one meetings on a weekly basis and offline feedback.

• Led digital customer experience to reduce customer churn rate with a focus on developing predictive ML models for mortgage refinance and new purchase propensities. • Automated mortgage origination process by utilizing text mining techniques on the historical loan data, resulted in a significant reduction of underwriting duration.• Identified growth opportunities for the data science team by collaborating with leadership to implement AI solutions for business use cases.

• Supported clinical trials to secure $30M+ series funds from BARDA (government organization) and private investors by designing in-house framework for medical image classifications with state-of-the-art deep learning models (Segnet/CNN/FCN). • Led research to bring medical image classification accuracy to 95%+ by experimenting with the latest Deep Learning models, leveraging new modeling features and creating product development roadmap.• Architected in-house database to support full scale clinical trials and enable sustainable data science development.

• Led data science research to discover new particles at the Large Hadron Collider (LHC) in collaboration with 10+ universities.• Developed data science framework in C++ and Python, which allowed scientists to democratize research on big data from the LHC.• Created novel data driven algorithms to enable new physics searches, which were published in scientific journals.• Held a leadership position in the collaboration to liaise data science activities between 20+ universities.• Managed firmware and C++ software development for the CMS pixel detector upgrade at the LHC.• Developed software to support hardware communication within the microTCA ecosystem.• Supervised undergraduate/graduate students in data science and research.

While obtaining my PhD at the University of Florida, I was awarded an opportunity to continue my research at the Large Hadron collider (LHC) at CERN in Geneva, Switzerland. My data science research involved uncovering particle physics world beyond our current understanding by analyzing large set of data from the LHC collider. Being part of an elite scientific organization of +3000 scientist from all over the world, I led a development of critical data science for discovering exotic new particles in the LHC data using C++, Python and distributed computing. Results were published in top scientific journals and the results have been presented in various conferences. My day-to-day activities included data management, data science research, development of data driven algorithms, hypothesis testing and presenting my work to the collaborators.