Empower customers to bring their generative AI visions to life.

• Developed and implemented deep learning (including generative AI) methods to accelerate engineering design processes.• Played a key role in launching a new service that enhanced customer experience in training ML models with synthetic data. Spearheaded research in AI-based image-to-image translation and formulated statistical methods for synthetic data evaluation.• Owned the entire project lifecycle, from proof of concept (POC) to production, collaborating closely with software engineers to write production-grade code.

Advised external and internal clients on innovative data solutions to achieve critical business goals.• Led a data science team in employing ML and natural language processing (NLP) techniques to automate the employee function-mapping process, enhancing operational efficiency.• Played a key role in facilitating multi-billion-dollar mergers by developing novel data science solutions to streamline the integration of HR and financial data associated with M&A activities.• Innovated an internal web application that generated customizable data visualizations (word clouds, organization charts, correlation plots, etc.), empowering hundreds of colleagues to quickly derive data insights to support decision-making.

Used advanced data analytics methods and technologies to impact patient care. Communicated statistical results and presented data intuitively to non-technical audiences through innovative data visualization and web applications. • Used machine learning to improve patient risk prediction models used by clinical staff to improve healthcare delivery and reduce the number of hospital admissions.• Developed an HR web application (using R Shiny) that provided user-friendly search functions, word clouds, and text analytics insights into confidential employee engagement survey results. • Led innovative research into physician referral networks using publicly available CMS data.

Selectively chosen (under 3% acceptance rate) to attend an intense 8-week data science fellowship. Benefited from exposure to state-of-the-art data science technology and the best minds in the discipline. Completed assignments on machine learning, natural language processing, web scraping, SQL, time series, MapReduce, and web development, using Python, Hadoop, Spark, and Scala.

Built machine learning models to predict 5 million individuals’ healthcare costs for the next year using their current pharmacy utilization, medical condition, and demographic data.

Performed data analysis to facilitate staffing and scheduling decisions for multiple call centers serving a 100 million-member base nationwide. Created groundbreaking interactive charts on historical call data.

Used Java to implement algorithms to measure similarities between 2 policy images, aiming at identifying policy images that represent the same policy in different databases without using database primary keys.