Ya Liu

Resume

Willing to relocate

Arlington, **202, VA

H 202-***-****

B adhp8l@r.postjobfree.com

GitHub: https://github.com/yaliu777,

LinkedIn: https://www.linkedin.com/in/ya-liu-733817151/ Education

12/2020 M.S. in Data Science, George Washington University, Washington, DC,USA. 06/2018 B.S. in Accounting, Southwestern University of Finance and Economics, Sichuan,China. Technical Skills

Languages: SQL, Python, R, SAS

Framework & Tools: Pytorch, TensorFlow, Tableau, Power BI Modelling: Neural Network, Classification, Clustering, Natural Language Processing

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Experience

05/2020-

08/2020

Machine Learning Intern, Cambium Learning, Washington DC, USA.

{ Utilized deep neural network to recognize speech in Python(Pytorch).

{ Built algorithms to preprocess data, transcribe audios, finetune pre-trained models, and abstract encoder output from the models based on up-to-date toolkit, NeMo and ESPNet.

{ Constructed metrics functions to evaluate and compare the transcriptions of different models. 07/2019-

08/2019

Statistician Intern, Equal Employment Opportunity Commission, Washington DC, USA.

{ Developed algorithm in R to apply Statistical Disclosure Limitation (SDL) techniques to pre-post enterprise micro-data in order to protect data privacy.

{ Performed data validation by statistical analysis of identification risk and data utility.

{ Produced heatmap to visualize the change before and after the treatment to data. Academic Projects

05/2020 Blood Cell Detection Using Faster R-CNN.

{ Utilized Faster R-CNN to detect malaria infected cells in blood cell images.

{ Coded to prepare data into the required format, fed data into model, and reached mAP 0.8677.

{ Fixed errors and improved the GitHub repositories, and added documentation in terms of environment setup. 11/2019 Classification Model on Credit Default Risk.

{ Conducted exploratory data analysis and performed data cleaning in Python.

{ Performed feature engineering and selected features by percentage of missing values, correlation, and feature importance.

{ Selected the best model, random forest, and interpreted it by feature importance plot. 04/2019 Explore Factors on Compensation Outcome for Wrongly Convicted People .

{ Cleaned data and calculated summary statistics in R.

{ Developed generalized linear model on whether exoneree will file/prevail a claim, and plotted ROC curve to estimate goodness of fit.

{ Quantitatively evaluated the effects of variables by interpreting odds ratio. 03/2019 Database and Data Visualization Based on Product Data.

{ Imported customer, order and product tables into MySQL, conducted advanced queries and stored them using the stored procedure.

{ Called the stored procedure in Tableau and visualized data to explore the association between promotion and sales volume of products and derive key metrics of different products. Core Courses

Machine Learning, Natural Language Processing, Data Mining, CS Foundation, Data Warehousing, Data Analysis, Applied Linear Model, Mathematical Statistics, Financial Management, Marketing Research Selected Honors and Awards

2018, 2019 Deans Fellowship Award, George Washington University. 2016, 2017 Third-class Scholarship, Southwestern University of Finance and Economics.

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