Qianmian Gai

424-***-**** # advwff@r.postjobfree.com ï linkedin.com/in/qianmian-gai/ § github.com/qianmiangai

Education

University of Southern California Sep. 2021 – May 2023(exp.) Master of Science in Applied Data Science, GPA: 3.8/4.0 Los Angeles, CA Pepperdine University Sep. 2017 – May 2021

Bachelor of Science in Mathematics, GPA: 3.8/4.0 Malibu, CA Bachelor of Art in Art History, GPA: 3.6/4.0

Relevant Coursework

• Algorithms Analysis

• Knowledge Graph

• Python Programming

• Data Mining

• Database Management

• Information Retrieval

• Machine Learning

• Statistics

Technical Skills

Languages: Python, R, Java, JavaScript, Spark, Scala, C++, HTML, CSS, SQL, SPARQL, Cipher, Latex, Matlab Technologies/Libraries: AWS, Ajax, ApacheSpark, Bash, Bootstrap, Django, Firebase, Flask, Git, Hadoop, Linux, MongoDB, MySQL, Neo4j, Node.js, PostgreSQL, PyTorch, Pyspark, React, Redis, Scikit-Learn, Scrapy, SpaCy, Vue.js Experience

National Bureau of Statistics of China Nov. 2020 – Jan. 2021 Data Scientist Intern, Statistics Department Binzhou, China

• Used Multi-class Linear Regression and K-Means classification to predict citizen income and housing prices. Result helped financial department to implement the incentive plan during the COVID-19

• Developed a Tableau dashboard to visualize the development of Binzhou city, ranked No.1 over 300+ competitors

• Wrote procedures to retrieve and update a database similar to MySQL. Significantly enhanced the working efficiency of the department by automating daily query executions Zhongtai Securities May 2020 – Aug. 2020

Fund Manager Assistant, Financial Portfolio Management Department Jinan, China

• Performed profit forecast using mathematical models and provided portfolio allocation suggestions by exploring and extracting data from Bloomberg and Wind Economic Database on a daily basis

• Conducted research on the consumer goods industry, evaluated business environment, institutional and fiscal policies Projects

Stock Price Predicting TensorFlow, Scikit-Learn, Pandas Sept. 2021 – Jan. 2022

• Built a stock price predicting system to forecast forward 3-day return and forward 5-day return

• Used a neuro-symbolic model by combining tree-based classification and deep learning model

• Fine-tuned the model by cross validation and model achieved positive outcomes for the target companies Artlink spaCy, Neo4j, Jinja, Streamlit Sept. 2022 – Dec. 2022

• Created a knowledge graph for over 20,000 contemporary artworks, utilizing Streamlit to show the outcome

• Auto-extracted artists’ information from biographies using spaCy. Linked artists’ personal websites and Instagram with their artworks using string matching algorithms, resulted a high precision of 87%

• Designed the Knowledge graph ontology of 16 semantic types, visualized the graph with Neo4j toolkit Recommendation System PySpark, Scala Dec. 2022 - Feb. 2023

• Build a hybrid recommendation system using Collaborative filtering to predict the ratings for user and business

• Model reached high accuracy with a RMSE of 1.23

Publication

The Impact of Social Media Activity on Nonprofit Donations in China Oct. 2017 – May 2018

• Scraped the massive social media comments and selling numbers of the ”Free-Lunch” non-profit program

• Analyzed the relationship between people’s attitudes and the selling outcome with advance mathematical models

• Article published on VOLUNTAS, URL: https://doi.org/10.1007/s11266-019-00168-7 Honors/Activities

• Student worker as Course Producer of Machine Learning class at University of Southern California (2022 - Present)

• Volunteered to help K-12 Computer Science education in Viterbi Impact Program (2021 - 2022)

• Recipient of Blanche E. Seaver Scholarship and Natural Science Scholarship at Pepperdine University (2018 - 2020)

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