Enterprise Data Scientist
Current• Provide machine learning on large datasets and in-depth statistical analyses, behavior pattern recognition using AzureML. Provide statistical data analysis such as linear models, multivariate analysis, sampling methods, and complicate data mining.• Lead division's data visualization project. Translate business questions and using statistical techniques to arrive at an answer using available data. Provide machine learning modeling, such as factor and clustering analyses. Interview section managers and SMEs to collect their business requests for their MBR performance. Build Power BI dashboard.• Lead and worked on the project of improving SQL query performance for multiple teams. Re-write slow SQL scripts.• Translate complex SQL programs from PL/SQL to T-SQL. The original PL/SQL programs include the customized functions, and we don't have the source code for these functions.• Lead and worked on the project to convert email version of reports to Power BI.• Re-engineering Microsoft Access queries and ETL the datasets for their CTR data migration.• Direct a UW student team to finish a machine learning modeling project. Introduce principle component analysis, cluster analysis, decision trees and Azure ML to the student team. Prepared the research datasets using SQL and Python. Select statistical tools given a data analysis problem. This project won the second place in their capstone project competition.• Provide statistics training to the SME’s in F&A Division.• Design and develop multiple Power BI dashboard or Power BI reports for Division level project.
