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Hi, I'm Annie! 👋

As a recent MSc graduate in Information Systems, I am passionate about leveraging technology to solve business challenges. With expertise in cloud technologies ☁️ and a strong technical skill set, I am eager to contribute to a dynamic organization that fosters growth and innovation.

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Skills

Programming

Python
SQL
JavaScript
HTML
CSS

Technologies

Git
Linux
Docker
AWS Services
Power BI
Tableau
Office

Proficiencies

Data Analytics
Technical Support
Cloud Support

Education

University College Dublin Logo

University College Dublin

MSc Information Systems (2:1)

Dublin, Ireland

Sep 2023 – Dec 2024

Xi’an University of Architecture and Technology Logo

Xi’an University of Architecture and Technology

BEng Landscape Architecture

Xi’an, China

Sep 2018 – Jul 2023

Experience

Data Analyst

Feb 2025 – Present

Peroptyx · Dublin, Ireland

  • Verified mapping data for critical navigation applications and ensured navigation routes and points of interest (POIs) were accurate and reliable.
  • Identified and resolved discrepancies in machine learning (ML) generated responses, significantly reducing model error rates.
  • Carried out ISO-certified Standard Operating Procedures and maintained rigorous quality standards for data processing workflows.

Innovation Academy Teaching Assistant

Oct 2023 – Dec 2024

University College Dublin · Dublin, Ireland

  • Taught 3D printing and VR courses to over 50 students and supported the lead instructor with lesson planning, material preparation, and classroom management.
  • Provided technical support to students during practical sessions and helped troubleshoot technical issues.
  • Collected and reviewed student feedback and prepared course materials.

GIS Data Analyst Intern

May 2022 – Jul 2022

Shaanxi Institute of Urban & Rural Planning and Design · Xi’an, China

  • Created dynamic dashboards with Power BI and presented actionable insights that improved resource allocation efficiency using PowerPoint.
  • Integrated ecological restoration data into urban planning projects and performed statistical analysis on geospatial data.
  • Built 3D regional models with ArcGIS and designed street optimization plans using traffic flow data.
  • Collaborated with team members to develop detailed reports with optimized regional plans, resulting in clear and actionable recommendations for government agencies.

Data Analyst Intern

May 2020 – Aug 2020

TAL Education Group · Xi’an, China

  • Scraped TikTok shops data using Python scripts and created shop comparison dashboards with Power BI.
  • Increased unique website visitors by identifying and analyzing high-impact keywords from 2,000+ trending TikTok video titles.
  • Collaborated with data engineers to develop automated data pipelines and data cleansing scripts, resulting in improved data quality for a machine learning model that analyzes TikTok advertisement performance metrics.

Projects

Personal Website

Mar 2025

  • Built a static resume website using HTML and CSS, deployed on Amazon S3 as a static website with HTTPS enabled via CloudFront.
  • Implemented a visitor counter using JavaScript, DynamoDB, and an API built with AWS API Gateway and Lambda.
  • Used Python and the Boto3 library to write Lambda functions for database interactions and integrated tests for the backend code.
  • Defined infrastructure as code using AWS SAM (Serverless Application Model) and set up CI/CD pipelines with GitHub Actions for both front-end and back-end updates.
  • Configured a custom DNS domain using Amazon Route 53 to point to the CloudFront distribution.

Technologies Used:

AWS (S3, CloudFront, Route 53) DynamoDB API Gateway Lambda AWS SAM HTML CSS JavaScript Python Boto3 GitHub Actions

Machine Learning Project for News Classification

Jun 2024

  • Processed and analyzed a 100k+ entry news dataset for model training and evaluation.
  • Preprocessed data using Pandas and Numpy: handled missing values, engineered features (e.g., text length), and converted text fields, improving data quality and model accuracy.
  • Trained and evaluated models (Random Forest, Naive Bayes, CNN with PyTorch), achieving 85% accuracy through hyperparameter tuning and cross-validation.
  • Visualized data distributions and model metrics using Matplotlib and Seaborn, providing insights on trends and effectiveness.
  • Integrated transformers for advanced NLP tasks, enhancing performance on complex categories like “Weird News” and “Travel.”

Technologies Used:

Python Pandas Numpy PyTorch Scikit-learn Matplotlib Seaborn Transformers (NLP)