About Me

About Me#

info

jlee2843 | jennyjeeun | jenny.jeeun@gmail.com | Resume

Introduction#

Greetings! I’m on an exciting journey in the Master of Data Science program at the University of British Columbia, fueled by a solid foundation in statistics and neuroscience from my undergraduate days. I thrive on exploring the intricacies of data, uncovering trends, and seamlessly applying those insights in unexpected domains.

My latest role in the relam of data science was working as a Data Science Intern at Teck Resources Limited. There, I delved into the world of Hugging Face transformers and the BERT model, tackling NLP challenges with gusto. When I am not exploring through data, you’ll often find me indulging my creative side by sketching and listening to music across various genres.

I am thrilled to share my data journey with my portfolio! Please feel free to reach out through any of the contact information above if you’d like to chat with me. 🚀🎨🎶

Skills Toolbox#

⌨️ Programming Languages

  • Python

  • R

  • Java

  • SQL (PostgreSQL, MySQL)

📈 Data Analysis

  • Data wrangling with pandas and numpy

  • Data retrival and management with SQL

  • Static visualization with matplotlib and seaborn

  • Interactive dashboards with plotly Dash, streamlit and altair

📊 Machine Learning

  • Supvervised learning

  • Unsupervised learning

  • Ensemble models

  • Neural networks

  • Deep learning

  • Familiar working with scikit-learn, scipy, PyTorch, Tensorflow, NetworkX

Career#

University of British Columbia | Food Sustainability Data Analyst

09/2023 - Present

▸ Part-Time | Python R Git GitHub Docker

Description
  • Engineered an automated workflow to evaluate the cumulative greenhouse gas emissions resulting from all procurement items acquired and utilized by UBC Food Services and AMS.
  • Implemented machine learning models to gauge UBC’s ability to achieve the Climate Action Plan 2030. In cases where meeting the goal is doubtful, the models offer recommendations to reduce annual greenhouse gas emissions.

University of British Columbia | Graduate Teaching Assistant

09/2023 - Present

▸ Part-Time | R Git GitHub

Description
  • Member of the teaching team for STAT 200 (Elementary Statistics for Applications) and DSCI 100 (Introduction to Data Science) at UBC.
  • Attended lectures to address students’ questions in real-time. Facilitated a lab section, guiding students through weekly lab materials. Assessed and graded student exams and assignments.

Teck Resources Limited | Data Science Intern

01/2023 - 08/2023

▸ Full-Time | Python Git GitHub Docker Databricks AWS

Description
  • Developed statistical solutions to address machine learning model performance degradation resulting from data drift. Automated the process of re-scaling incoming data values upon detecting data drift.
  • Explored and implemented alternative machine learning models aimed at replacing the existing high-performance but costly BERT model. Investigated models with enhanced interpretability, such as K-means clustering, logistic regression, and DBSCAN clustering.

University of British Columbia | Climate-Friendly Sustainability Data Analyst

08/2022 - 04/2023

▸ Part-Time | Python R Git GitHub Docker

Description
  • Engineered an automated workflow to evaluate the overall impact of newly added food items to the UBC Food Services database.
  • Categorized all food items offered by UBC Food Services into green, yellow, and red based on the total greenhouse gas emissions produced by 100g of each menu item.
  • Labeled newly added food ingredients in the UBC database.
  • Developed a web-based application for Food Services staff to efficiently search for climate-friendly labels.The application incorporates dynamic graphs that change based on the selection of particular residence halls or vendors.

Ciena | Machine Learning and Modelling Intern

09/2022 - 12/2022

▸ Full-Time | Python PostgresSQL Bigbucket NetworkX

Description
  • Enhanced an outdated artificial neural network model through real-time data analysis. Conducted comprehensive testing using six different methods and generated a detailed report comparing the performance of each approach.
  • Collaborated with colleagues to develop an interactive app using Plotly Dash. This app enables clients to effortlessly monitor their current network traffic and explore future predictions.

Cybera Inc. | Data Science Intern

04/2022 - 03/2024

▸ Full-Time | Python R Git GitHub

Description
  • Analyzed, wrangled, and visualized data sourced from an open-source database on trending topics. Gained exposure to various Python and R packages for visualization, including Matplotlib, Seaborn, Plotly, Plotly Dash, and Ggplot.
  • Collaborated with colleagues to create hackathon content for Albertans. Prepared and processed open-source datasets to serve as valuable resources for a data science hackathon.
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