Natalie Kwong
About Natalie Kwong
Natalie Kwong is a Data Science/Visualization Intern with a Bachelor of Science in Cognitive Science and a minor in Computer Science from UC San Diego. She has experience in data wrangling, automation, and visualization, and has worked with various organizations including Deckard Technologies and Qualcomm Institute.
Work at Deckard Technologies
Natalie Kwong serves as a Data Science/Visualization Intern at Deckard Technologies, a position she has held since 2021. In this role, she focuses on data analysis and visualization, contributing to various projects that enhance the company’s data-driven decision-making processes. Her responsibilities include developing tools and methodologies to streamline data handling and improve visual representations of complex datasets.
Education and Expertise
Natalie Kwong earned her Bachelor of Science degree in Cognitive Science with a specialization in Machine Learning from UC San Diego, where she studied from 2019 to 2023. She also completed a minor in Computer Science. Prior to her university education, she graduated from Monte Vista High School in 2019. Her academic background equips her with a strong foundation in data science and machine learning principles.
Background in Data Science and Visualization
Natalie has developed significant expertise in data science and visualization through various internships and projects. She has automated the creation of individual graphs for California counties, detailing rental attributes using Python. Additionally, she utilized PowerBI to create an animated map dashboard that illustrates company growth over time, showcasing her ability to transform data into actionable insights.
Previous Work Experience
Before her current role at Deckard Technologies, Natalie worked as a Computer Science and Math Tutor at Art of Problem Solving from 2020 to 2021. She also held a supervisory position at Papa Murphy's Take N Bake Pizza from 2017 to 2020. These roles provided her with valuable experience in leadership, communication, and problem-solving, which she applies in her current data science endeavors.
Technical Skills and Projects
Natalie has demonstrated proficiency in various technical skills relevant to data science. She developed Python functions to standardize the wrangling of CSV and GeoJSON files for mapping data related to real estate, COVID, and weather. Additionally, she created a Docker image executed through AWS Batch to automate data updates for a California heat map, illustrating her capability in utilizing modern technologies for data management.