Loan Robinson

Loan Robinson

Senior Data Engineer / Data Scientist at Astellas

Loan Kim Robinson is a Senior Data Engineer/ Data Scientist at Astellas. She is also an Associate Professor and teaches Master Applied Analytics at Columbia University in New York.

She is interested in interactive statistical graphics, statistical computing and modeling. She is a highly analytical and solution-oriented professional with 9+ years of demonstrated success in statistical analysis and presentation, hands-on experience working with patient, biotechnology, and pharmaceutical drug data. She is successful in driving best-in-class visualization and reporting, as well as, explaining statistical methods to non-statistical people that results in effective understanding, cost savings, and efficiency. She also has experience with working across different levels of leadership to leverage statistical testing, business intelligence, and data- driven analytics.

Her favorite programming languages are R and Python, she developed many R shiny applications at her previous and current work. You can find all of her applications for her book at https://kimloanrobinson.shinyapps.io/rshinybook_web/

She was born in Ho Chi Minh City, Vietnam, and emigrated to the United States in 2008, she wasn't able to afford even a sandwich. She is the embodiment of tenacity and determination, having overcome untold obstacles and struggles with incredible perseverance. 7 years later, she earned her MS in Statistics. From there, she worked tirelessly and passionately to become an expert in various fields of Statistics, Mathematics, Business Intelligence and Data Science.

Sessions

    Data Analytics and BI Intermediate

    R/R Shiny is rapidly gaining significant traction in the finance industry due to its powerful features and capabilities. There are many R packages designed for financial data analysis and visualization. They make it easy to import, clean and manipulate data. They also support performing complex calculations, statistical analyses, and generating insightful, beautiful visualizations to gain insights into market trends, risk management, and portfolio optimization. Time series analysis and machine learning are also much easier to handle in R.