Data Scientist Intern

NGUYEN QUYNH KHANH HA

DATA SCIENTIST INTERN

Date of birth: 11/09/2002

Phone: 085******* Email: ******************@*****.*** Linkedin: linkedin.com/in/nguyenquynhkhanhha

Github: https://github.com/KhanhHa1109

OBJECTIVES

A motivated, teamwork-oriented, and accountable Data Scientist intern. I enjoy to drive the effectiveness of business through making recommendations based on data findings, eager to learn new technologies and best practices to become a better Data Scientist. EDUCATION

UEH University

2020 – Present

Major: Data Science

GPA: 8.53/10

CERTIFICATE

04/01/2020 IELTS 6.5

EXPERIENCE

Wiziin

(Data-driven Investment

Platform)

06/2022 – 11/2022

Research Analyst Intern

_ Produced research reports, including research of investment and technology field, especially blockchain, DAO (Decentralized Autonomous Organization), Web3, crypto, angel investors and venture capital related trends.

_ Identified and procuring investable opportunities. _ Compiled reports and articles for internal consumption. _ Performed data analysis, visualization, econometric studies. EXTRACURRICULAR ACTIVITIES

Institute of Business

Research – UEH

University

11/2021 – 03/2022

Translation Collaborator

_ Translated Research papers in Economics given by professors. _ Proofreaded documents for grammar, spelling and puctuation accuracy.

_ Used Turnitin to check plagiarism and paraphrasing documents. UNIVERSITY PROJECTS

Data Science

(Online Retail Analysis)

_ Customer segmentation (using K-prototype clustering) to find customer groups with similar purchase behaviors.

_ Found association rules (Market Basket Analysis using FP- Growth algorithm) to see which set of products were often bought together.

_ Built Time-series models to find seasonal patterns and trends of product items.

Data Crawling and

Analysis

(Youtube data crawling)

_ Crawled ~5000 Youtube video statistics and >20.0000 comments through Youtube Data API.

_ Built Topic Models to extract hidden video topics (combining Autoencoders Deep Learning, BERT word-embeddding, and traditional clustering techniques)

_ Applied LDA topic modeling to build content-based recommendations system.

Natural Processing

Language

(Sentiment Analysis on

Customer Reviews)

_ Sentiment analysis using supervised machine learning method

(Logistic Regression & Naive Bayes classification, implemented in NLTK library) to predict positive and negative customer feedback. _ Obtained a performance score of ~88%

TECHNICAL SKILLS

Programming Languages: Python, R, C#

Database Management Systems: MySQL, PostgreSQL

Business Intelligent Analysis: Power BI, Orange Diagram/Flowchart: draw.io

HPC: WMware, docker

Design/Edit video: Adobe Photoshop, Premiere, After Effects HONORS & AWARDS

UEH Top Student Scholarship in Fall semester 2020 and Spring semester 2022

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