Kalee Li

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Data, Solution, and Process Engineer and Analyst specializing in data solutions, system performance analysis, bottleneck identification, and process optimization. I develop and implement data infrastructure, ETL pipelines, and technical solutions to drive efficiency and enhance analytics.

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Welcome to My Cooledtured-internship projects overview

My Experience at Cooledtured

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I’ve been with Cooledtured Collection since October 2024, initially joining as a Data Research Analyst intern for a three-month program. However, I chose to stay because of the connections I built with my peers and stakeholders and the opportunity to take on higher-level projects that challenged me to grow technically and professionally.

Over time, I transitioned into a role focused on system architecture, data engineering, and automation. I took on projects that involved designing and implementing data pipelines, managing infrastructure, and developing solutions to make workflows smoother. I also worked on optimizing processes and automating tasks, making our team more efficient. Each challenge I faced contributed to my growth, and every project taught me something valuable.

To me, Cooledtured has always felt like more than just a workplace. It’s a supportive community where we all learn from each other. Our twice-weekly QA meetings with my team and leader create space for continuous growth and the monthly Town Hall meetings give us a chance to connect with interns from other teams, share ideas, and find new opportunities to collaborate. Outside of these required meetings, my teammates and I would meet to discuss planning and brainstorm ideas, which has made our collaboration even stronger.

Throughout my time here, I’ve mainly used Google Apps Script and Python to build efficient solutions, Google Sheets Query functions for dynamic data manipulation, and real-time reports. For data analysis, I’ve used R and for visual storytelling and data visualization, I’ve worked with ggplot2, Tableau, Genially, Figma, and Lucidchart to present complex data in a clear, engaging, and accessible. I created interactive infographics with Genially and Figma and used Lucidchart for flowcharts and process diagrams.Additionally, I built a user-friendly landing page and analysis dashboard using Google Sites to ensure easy access to information.

Being part of Cooledtured has not only strengthened my technical skills but also helped me grow personally and professionally in meaningful ways.

Feel free to browse my project content table and explore any project that interests you. Most of the completed projects are uploaded, and more will be added soon as I continue working on new ones.

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Projects Content Table

Competition Analysis for Inspiration: BoxLunch

(Solo Project)

Project Overview: This project analyzes BoxLunch as a source of inspiration, identifying key strategies that drive its success. By examining its strengths, weaknesses, opportunities, and threats (SWOT), along with marketing efforts, consumer engagement, and store expansion, we gain valuable insights into best practices for brand growth. The analysis leverages web scraping, Google Trends, and manual data collection to ensure a comprehensive understanding of BoxLunch’s market presence.

Research Question: How do BoxLunch marketing strategies, including social media engagement, store growth, and employee satisfaction influence consumer behavior and enhance customer engagement?

Data Collection Methods: To ensure comprehensive analysis, various data sources were utilized:

Project Reflection: This analysis provided valuable insights into how BoxLunch engages its audience, expands its physical presence, and manages employee satisfaction to drive consumer loyalty. By combining data scraping, Google Trends analysis, and manual tracking, we identified key marketing strategies that contribute to the brand’s success. The study highlights the effectiveness of exclusive products, influencer marketing, and community engagement in fostering strong customer relationships. These findings offer inspiration for refining marketing approaches in similar industries.

Self Reflection: The BoxLunch Competition Analysis for Inspiration was my first project at Cooledture. Although this was a Solo Project, I was lucky to have a supportive team that guided me through the process and helped me stay focused on my research question, specifically identifying what types of data would be most relevant. During this project, I learned how to scrape data using Selenium WebDriver and Python Reddit API Wrapper to collect the data I needed to better understand BoxLunch. Additionally, I used Google Trends for the first time to track shifts in consumer interest, and I conducted research to uncover the reasons behind the spikes and dips in interest.

Visual and Presentation: Below are links to Google Slide and Colab

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Social Media Insight and Content Analysis

(Team Project)

Description: This project focused on analyzing Instagram content from 2021 to 2024. The goal was to understand what types of posts performed best and how engagement varied across different content formats. Our main research questions were:

In addition to our data, we analyzed eight competitor companies to learn about their background, growth strategies, and social media performance.

We used these insights to make actionable suggestions to help the content team improve their formatting and content delivery.

Project Reflection: Throughout the project, we saw the importance of clearly defined research questions and aligning them with the available data. While Instagram Insights offered valuable metrics, the data lacked the level of detail we needed for deeper analysis. As a result, we manually reviewed and classified each post by content type to ensure more accurate and relevant insights.

One improvement we identified was updating the content team’s submission process. By adjusting the format to align with engagement metrics provided by Instagram, we can create a more complete dataset in the future. This will help support ongoing performance tracking and enable more meaningful analysis over time.

Self Reflection: This project taught me how bridge the gap between quantitative data and qualitative content insights. I realized that numbers alone don’t tell the full story - context, sentiment, and strategy play a huge role in audience engagement.

When we saw the limitations of the existing data, I took the initiative to suggest a change to the content submission format so that future data could be more easily linked to performance metrics. It felt great to contribute something that could make a long-term impact on how we track and improve content.

Overall, this experience strengthened my analytical thinking, attention to detail, and ability to connect data with real-world applications.

Visualization:

Presentation Video: Below are links to key parts of the presentation video:

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Bottleneck Analysis for Content Creation Team

(Solo Project)

Description: This project aimed to identify and analyze bottlenecks within the content creation team’s workflow in order to improve overall efficiency, clarity, and productivity. The analysis was based on my observations during team shadowing, and Agile-aligned suggestions. I investigated pain points in onboarding, communication, workflow visibility, and role-based training, with the goal of proposing actionable solutions.

Project Reflection: This project revealed that structural inefficiencies in the content creation team, such as disorganized resources, unclear instructions, and generic onboarding, led to confusion. Although a content creation process existed, it was spread across too many pages, leaving the team to piece things together on their own. Creating role-specific training and establishing clear workflows made the process easier to follow and helped the team work more effectively.

Self Reflection: Through this project, I strengthened my skills in process analysis, UX thinking, and Agile implementation. Shadowing the team helped me understand users at different experience levels, and creating structured, visual solutions improved my ability to communicate processes clearly. I also learned the importance of adapting onboarding and training to the unique strengths of a diverse team. This experience deepened my understanding of internal operations and increased my confidence in identifying and addressing organizational inefficiencies.

Presentation: Google Slides - Bottleneck Analysis

Presentation Video: Below are links to key parts of the presentation video:

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Data Team Optimization Strategy Project

(Team Project) Completed. Upload Soon

Description: This project focused on optimizing the data team’s structure, improving efficiency and collaboration, and aligning team efforts more closely with company goals. As the team transitioned from “Data Research” to a more defined “Data Team,” which included data analysts, data scientists, BI professionals, and data engineers, it became clear that we needed greater role clarity, stronger alignment with company objectives, and better use of each member’s technical expertise.

Project Reflection: The Data Team Optimization project addressed key structural challenges within the team, such as unclear roles, a lack of onboarding roadmap, and misalignment with company goals. By defining responsibilities, improving onboarding structure, and encouraging collaboration, the project led to more efficient workflows and better use of each member’s skills. Standardized documentation and proposal processes helped reduce confusion, while structured role exploration allowed interns to contribute more meaningfully. Overall, the project strengthened internal operations and improved the team’s ability to deliver high-impact, goal-aligned work.

Self Reflection: Since joining the data team in October 2024, I have gained a deeper understanding of how team structure, communication, and onboarding impact overall performance. Being part of the optimization project allowed me to contribute to meaningful improvements. I helped define roles and responsibilities, implement a structured onboarding process, and align team proposals with business priorities. I also worked on creating role-specific onboarding materials, a knowledge hub, and a roadmap template to standardize proposals and documentation. To improve deliverables, we added SDLC frameworks, researched technical tutorial links for the knowledge hub, and included project-based certificates as incentives for interns within the roadmap. Additionally, to support visibility and growth, we introduced an e-portfolio tutorial in the knowledge hub and a LinkedIn-sharing box on our member portal. This experience strengthened my ability to identify gaps, support team development, and contribute to impactful, goal-aligned solutions.

Presentation: Google Slides - Data Team Optimization Strategy Project

Automated Content ELT Pipeline

(Solo Project)

Description: The Automated Content ELT Pipeline project aimed to improve the data collection, processing, and analysis for the content creation team. We transitioned from Google Docs to Google Forms for content submissions, enabling easier data export as CSV files. The pipeline extracts, loads, and transforms the data, linking creators to their content via unique IDs and connecting with social media metrics. This setup facilitates detailed content and performance analysis, supports creating visual progress reports for creators, and helps identify platform effectiveness for various content types. T

Security The entire pipeline is automated using App Script, running updates every 10 minutes while securely protecting private information by anonymizing creators with unique IDs. Additionally, the sheets are restricted throughout the entire ELT process (extracting, transforming, and loading) to prevent unauthorized access.

Project Reflection: Initially, the available data was limited and inconsistently formatted, necessitating the manual classification of posts by genre, content, and style to establish a reliable baseline. This project successfully addressed these challenges by restructuring data collection and processing methods. Transitioning from Google Docs to Google Forms and building an automated ELT pipeline enabled more accurate, unbiased, and in-depth analysis. Standardizing column names, removing duplicates, and validating data greatly improved overall data quality. The pipeline’s design supports continuous updates, protects sensitive information, and creates opportunities for future projects that combine qualitative and quantitative data to yield richer insights. Ultimately, the project optimized data workflows and laid a strong foundation for Cooledtured to use data as a strategic asset for growth and industry leadership.

Self Reflection: Working on the Automated Content ELT Pipeline has deepened my technical skills in data engineering, automation, and data quality management. I gained hands-on experience designing a system that balances data accessibility with privacy, ensuring creators’ information remains secure while enabling powerful analytics. Troubleshooting inconsistencies during the transformation phase strengthened my problem-solving abilities and attention to detail. I also developed a stronger understanding of how structured data pipelines can directly impact business insights and strategic decisions. This project has increased my confidence in managing end-to-end data workflows and envisioning long-term value for data-driven initiatives.

Entity Relationship (ER) Diagram: Lucid Chart - Content Submission ERD

Presentation Video: Below are links to key parts of the presentation video:

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Forms Tracker

(Solo Project) Completed. Upload Soon

Description:
Security
Project Reflection: Self Reflection:
Tutorial Video:

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HR Automation System (Internship Recruitment System)

(Solo Project)

Description: The HR Automation System is a comprehensive recruitment management solution designed to streamline the internship hiring process by reducing manual tasks and centralizing candidate tracking. The system integrates Gmail, Google Sheets, Google Drive, and Python-based NLP tools to automate onboarding emails, interview scheduling, resume parsing, and applicant status updates. It uses Gmail API to bypass email limits, custom Apps Script workflows for data movement and filtering, and NLP-driven resume scanning to extract key details from uploaded files. Real-time data consolidation to give the HR team an accurate and centralized view of each applicant’s progress tracking, making large-scale recruitment more efficient, organized, and secure.

Project Reflection: This project solves key challenges faced in high volume internship recruitment—namely, inefficiency, miscommunication, and human error. By automating email communication, interview tracking, and resume data extraction, the system eliminates repetitive work and minimizes oversight. It has also proven scalable, allowing the team to manage hundreds of applicants without increasing manual workload.

Self Reflection: Building this system deepened my skills in workflow automation, data integration, and secure access management. I learned how to effectively combine APIs, Apps Script, and Python tools to build a real-world, end-to-end solution. I also became more intentional about code organization and system design, structuring features around real user needs. Through troubleshooting and iteration, I improved my ability to think systematically, debug across platforms, and design scalable tools that make a measurable impact on team productivity.

Presentation:

Presentation Video: HR Automation System V1

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Other Projects

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