Machine Learning Data Science

Dillon Tsien

******.*****@*******.*** 206-***-****

Summary

• Recent Economics graduate with a focus in econometrics and data science. A passion for using datasets and techniques such as machine learning to uncover important trends in data and creating valuable visualizations with them.

• Skills: Econometric modelling, machine learning, price optimization, data wrangling and reshaping

• Applications: R, Tableau, Excel, Stata, PowerPoint, Word Education

University of Washington, Seattle

Bachelor of Science in Economics September 2019 – June 2022 Minor in Data science

• Cumulative GPA: 3.77/4.0

• Relevant coursework: Econometric Theory and Applications, Data Science for Pricing, Computational Finance, Game Theory

• Honors: Dean’s list (2019-2022)

Projects

King County House Sales Project March - June 2022

• Filtered and merged datasets in R from the King County Department of Assessments to prepare one large dataset for machine learning

• Used multiple types of supervised machine learning such as a linear regression, lasso, and random forests to evaluate and quantify the different effects of house features on the sale price

• Presented our findings and the merits of each type of supervised learning in a report Orange Juice Sales Project January – March 2022

• Evaluated the effect of different factors of orange juice cartons on the quantity sold

• Ran regressions in R and Stata on the different variables along with creating insightful diagrams to display the effects of each feature on the number of sales

• Presented caveats and ways to improve the regressions Retail Individual Sales Project September – December 2021

• Filtered and manipulated an individual sales dataset from an online retailer to discover trends in things such as location, time, or amounts

• Data wrangled and created visualizations in R to uncover essential insights

• Created presentation with various graphs and tables to effectively present findings and recommendations to improve the retailer’s sales

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