Trang Le

adchmm@r.postjobfree.com ***- ***-**** linkedin.com/Trangle github.com

Graduate with a strong background in statistical analysis, data analysis, data visualization, data mining, and model building seeking an opportunity as a data scientist. Education

University of St. Thomas M.S. in Software Engineering 2016 - 2020 Hue University, Vietnam B.A. in Applied Linguistics 2011 - 2015 Skills

Programming languages: Python, Java, SQL.

Tools/ Libraries/ Technologies: Tableau, SAS, MatplotliB, Keras, Tensorflow, AWS, OpenCV, Google Cloud Platform, Jupyter Notebook, RStudio, Eclipse, Pyspark, Spark ML, ElasticSearch, Data Scraping, Docker, Numpy, Pandas, Scikit- learn, TF-IDF, NLTK, RAKE, Microsoft Office Suite. Databases: MySQL, Spark SQL, HDFS, MongoDB.

Work Experience

Graduate Research Assistant JAN 2020

• Assisting in creating a Machine Learning classifier that helps identify complicated software and demonstrating the impact that complicated software has on software development. Data Analyst Intern - FFEN FEB 2020

• Report Creation & Data Analysis: Conduct data entry using Microsoft Excel to create food shelf specific food sourcing analysis reports to identify key metrics and craft underlying structures from data.

• Identify Potential Strategic Planning: Develop recommendations that promote more fiscally responsible operations and a healthy, high quality product mix for food shelf customers by using a variety of data evaluation tools and techniques.

Related Experience

Cancer Predictor App/ Python - https://cancer-predictor-app.herokuapp.com/ DEC 2019

• Helped physicians correctly predict whether or not a suspicious lesion seen in a mammogram is benign or malignant, in order to apply appropriate treating methods.

• Performed a variety of data analysis techniques for feature engineering. Built models with Machine Learning algorithms: SVM, Logistic Regression, Naive Bayes, KNN, XGBoost, Random Forest, and Decision Tree.

• Employed GridSearchCV for every model to search for hyper-parameters optimization and evaluated models using KFold cross validation.

• Achieved 90% accuracy. Deployed the application using Flask on Heroku platform. Performed an end-to-end lifecycle of Machine Learning development project. Sentiment Detector App/ Python - https://sentiment-detector-app.herokuapp.com/ DEC 2019

• Implemented a sentiment analysis model to identify whether a given statement is of contextually positive or negative sentiment.

• Employed NLTK and other libraries for feature engineering in text, and Word Embeddings for features representation. Applied Naive Bayes, Logistic Regression, Conv1D defined model, RNN in Tensorflow, and LSTM in Keras for this sequence classification problem.

• Obtained an accuracy of 85% and deployed the application with the end point REST API for end users. Event Designer/ Java/ Group Project NOV 2018

• Connected clients to decor choices that match their personal style and budget to a florist that could provide the client's unique vision to their event.

• Utilizing Test-Driven Development and several design patterns and design principles. Applied Java 8 and Java Swing for GUI.