Mastercard, a pioneering force in the financial industry and an expanding global technology leader, delivers innovative products and solutions that shape our future. Highlight of my achievements and duties:* Lead end-to-end, statistics and machine learning-focused financial analytics services with production data* Drive financial/FinTech innovations by leading the development of models and processes using state-of-the-art machine/deep learning* Inform executive decision-making by directing the design and implementation of proof-of-concept analyses for insights into financial/FinTech market trends* Manage transaction fraud monitoring projects with cross-functional contributions from Data Scientists, Data Engineers, Software Engineers, and Product/System Owners* Oversee the deployment and refresh of flagship fraud monitoring service gaining $0.5B revenue annual revenue* Support strategic initiatives and business intelligence products/services through AI by collaborating with senior leadership*Undertook multiple roles/sub-roles since the start of company, across multiple teams, both within and outside of USA

IBM is a global leader in technological innovation, driving progress through cutting-edge research and delivering world-class business solutions that redefine industry standards. Summary of my achievements and duties:* Engineered and deployed production-level machine learning pipelines with enhanced efficiency for multiple business units in IBM Cloud and Kubernetes PaaS* Delivered tailored, AI-driven software solutions for stakeholders leveraging big data analytics and predictive modeling * Led technical workshops and tutorials on cutting-edge technologies (e.g., Docker, Kubernetes), resulting in increased cross-functional adoption of new tools* Contributed to the development and maintenance of open-source cloud computing software with Agile best practices and DevOps automation* Ph.D. degree is required for this role *

Research Highlights: * Trained supervised machine learning classifiers (e.g. SVM) in the R and frameworks to identify breast cancer patients with a greater likelihood of chemotherapy response* Built deep learning feed-forward networks and LSTM using the Tensorflow/Keras/PyTorch frameworks to predict and characterize the fundamental gap in biomedical knowledge* Integrated “multi-omics” datasets (gene microarray, RNA-sequencing, mass-spectrometry proteomics) for testing novel hypotheses with the use of High Performance Computing (HPC) for publications in high-impact journals* Mentored undergraduate/graduate/professional students in big-data analytics and statistical modeling using R, Python, Shell & concepts in biostatistics & machine learningTeaching Roles:* Developed programming projects using publicly available datasets (e.g. Kaggle, UCI) for students to gain practical skills in implementing computer algorithms* Managed 70-90 undergraduate students each quarter by evaluating assignments and answering students’ questions during in-person or Zoom office hours* Authored solutions to theoretical problem sets and exams to reinforce students’ understanding of core concepts* Taught guest lectures in introductory (e.g. Python programming) and advanced topics (e.g. EM algorithm) * Supervised undergraduate teaching assistants and graders to ensure fairness and timeliness in grading and providing students with constructive feedback

Amgen is a biotechnology leader aiming to unlock the potential of scientific discoveries to improve patient lives. My responsibilities and achievements include:* Processed free-text consumer data using natural language processing (NLP) methods (e.g. Spacy, regex in Python & Java) and predicted categorical information using pre-trained language models (e.g. BERT) and LSTM neural networks to understand mechanisms driving consumer satisfaction* Estimated missing information in manufacture data using machine-learning (e.g. random forest) and deep-learning optimization via PyTorch, Keras, and sklearn implementations* Designed & executed computational experiments (e.g. A/B testing), performed statistical analyses and data visualization using Python and R to identify strategies for improving user experience

The Molecular and Behavioral Neuroscience Institute (MBNI) uses cutting edge approaches to advance the understanding of brain development and physiology for scientific discovery and clinical application.Responsibilities:* Computationally designed and experimentally applied the CRISPR-Cas9 technology to modify the genome and epigenome for understanding the mammalian biochemistry and neurobiology* Designed and executed molecular cloning, gene-expression and functional genomics experiments for testing hypotheses in molecular neuroscience