Shao Hsiang Chien

Junior in NTHU DSPMT, with the double specialties of quantitative finance and computer science. Enthusiastic about web development and data science.

  New Taipei City, Taiwan     Personal Portfolio

Education

2019 - 2023

National Tsing Hua University

Double Specialty Program of Management and Technology in Quantitative Finance and Computer Science

Skills

Web Development


  • HTML, CSS, RWD
  • JavaScript (ES6), React.js
  • Hooks, MUI

Data Science


  • Python, SQL
  • Pandas, Numpy, Seaborn
  • Tensorflow (Keras), SKlearn

Related Skills


  • Git version control
  • Chrome Dev Tool
  • Jupyter notebook, Colab

Relevant Experience

Jan 2021

NTHU DSPMT Commercial Competition   Second Place

Perform business analysis on a social enterprise, DiD HK, and propose a strategy to solve their issues regarding their lack of social influence and reputation.

Jan 2021 - Dec 2021

III Corporate Data Competition Top 5 in Group Pchome

Perform data mining on the sales datasets of Pchome to find their pain point and research for the prospective customers as well as their buy-back cycles.

Related Courses taken

• Introduction to Programming I (CS) — A

• Data Mining (ISA) — A+

• Statistics I (ECON) — A+

Work Experience

Sep 2020 - Jul 2021

Campaign Leader  NTHU Echo

Organize and host club-campaigns 

March 2021 - Aug 2021


Academy Leader  NTHU DSPMT Summer Camp

Organize the special courses of the camp, control the schedule, and design the programming course.

Jan 2022 - now


Frontend Developer  SUSU

Frontend development with React.js and connect to the backend APIs.

Projects

Pchome Sales Data Analysis

Perform data mining on the sales data of Pchome. Find out the prospective consumers and their buy-back cycles through EDA, RFM Model, and collaborative filtering. Formulate solutions with valuable insights from the analysis of data.

Netflix Drama Public Opinion Platform

Collect the scores on different dramas from different sites and the comments from Facebook and Dcard through web crawling techniques. Perform sentiment analysis on the comments with a self-trained deep learning model. The informations above and the statistical results are presented on a website made with Streamlit and Google Firebase.

Language


  •  TOEIC 950 — L 495 R 455
  • TOEFL 104 — R 29 L 28 S 22 W 25
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