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LisaLi525/README.md

README for Caiwen"Lisa" Li's Portfolio

Introduction

Welcome to my portfolio! I'm Caiwen (Lisa) Li, a Data Scientist and Applied Scientist with a passion for leveraging data to drive business insights. This README provides an overview of my background, skills, education, and professional experience.

About Me

Overview

I am an experienced Data Scientist with a strong background in machine learning, report automation, and business intelligence. My expertise spans various industries, including technology, tourism, retail, and digital media marketing. I am skilled in statistics, modeling, coding languages, digital marketing, reporting tools, databases, and machine learning algorithms.

Education

  • Ph.D. in Data Science (Expected Graduation Year: 2025)

    • Universiti Putra Malaysia, Kuala Lumpur, Malaysia
  • M.S. in Statistics (2016)

    • Hainan Normal University, Hainan, China
  • B.S. in Applied Mathematics (2013)

    • Hainan Normal University, Hainan, China

Publications

  1. C. Li (2016), "The securities market indicator for crash warning simulation optimization." Journal of System Simulation, Beijing, China.

  2. C. Li (2023), "Deep Learning-Based Recommendation System: Systematic Review and Classification," IEEE Access, vol. 11, pp. 113790-113835, 2023, doi: 10.1109/ACCESS.2023.3323353.

Special Courses

I have completed various courses in areas such as Functional Analysis, Topology, Measure Theory, Stochastic Analysis, Financial Mathematics, and more. Additionally, I attended statistics summer schools and earned certificates in e-learning programs related to machine learning and data science.

Certificates

  • Data Engineering with Google Cloud (Google Cloud, 2021)
  • IBM Data Science (IBM, 2020)
  • Advanced Google Analytics (Google, 2018)
  • Google Partners (Google, 2018)

Honors and Awards

  • IEEE CTSoc GOLD AWARD (Universiti Putra Malaysia, Nov 2022)
  • Innovation Scholarship (Hainan Province Ministry of Education, Nov 2010)
  • Challenge Cup Entrepreneurship Competition Bronze Medal Winner (China Ministry of Education Degrees and Graduate Education Development Center, Jul 2010)
  • Excellent Student Leader Award (Hainan Normal University, Jun 2010)

Professional Experience

Research Scientist at UPM (10/2022 – Present)

  • Conducting detailed summaries of articles on text mining techniques for recommendation systems.
  • Developing a recommendation framework, including offline pipelines, feature engineering, and user segmentation.

Data Scientist (Business Intelligence) at AWS (11/2021 – 9/2022)

  • Conducting in-depth data analysis to identify areas for business improvement at Amazon Web Service.
  • Utilizing machine-learning algorithms for product recommendations and marketing strategies.

Data Science Manager at BookXchange Inc. (4/2020 – 6/2021)

  • Leading data science projects and the development team to automate platform connections.
  • Providing pricing strategies and sales price forecasting for the sourcing and sales teams.

Data Science Manager at Zimmerman Advertising (7/2018 – 7/2019)

  • Utilizing Google and Adobe Analytics data to automate site performance reports.
  • Coordinating campaign-specific findings and recommendations for digital media campaigns.

Projects

I have worked on diverse projects, including customer insights, deal journey optimization, search engine optimization, automated reporting, forecasting, and recommendation engine development. Technologies used include AWS, Google Cloud Platform, R, Python, SQL, and various analytics and visualization tools.

Please refer to the Projects section in my GitHub repository for detailed information.

Contact

Feel free to reach out to me at caiwenli525@gmail.com. I am open to collaboration and discussion on data science, machine learning, and related topics.

Thank you for visiting my portfolio!

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  1. Retail-Store-Customer-Sale-Analysis Retail-Store-Customer-Sale-Analysis Public

    This R project conducts a comprehensive analysis of customer distances and sales for retail stores. Leveraging SQL server connectivity, it calculates distances, categorizes sales within specified r…

    R

  2. Basket-Analysis-Data-Mining Basket-Analysis-Data-Mining Public

    This Market Basket Analysis project in Python/R offers a versatile solution for uncovering purchasing patterns from transactional data. Utilizing powerful libraries like pandas, sqlalchemy, and mlx…

  3. FastTrack-Sales-Forecaster FastTrack-Sales-Forecaster Public

    FastTrack Sales Forecaster leverages ARIMA models for advanced time series analysis in fast food sales. It efficiently predicts future trends from historical data, aiding in strategic planning and …

    Python 1

  4. Retail-Traffic-Competitor-Analysis Retail-Traffic-Competitor-Analysis Public

    This R script analyzes Michaels store traffic, compares it with competitors, and assesses market share. Explore proximity, sales trends, and demographic insights for strategic decision-making.

    R 1

  5. Vendor-Boosting-Regression-Metric-Analysis-Random-Forest Vendor-Boosting-Regression-Metric-Analysis-Random-Forest Public

    The "Vendor Boosting Regression" project uses Random Forest regression to score vendors based on metrics like GSS and new subscriptions, identifying key performance factors through machine learning…

    Python

  6. Academic-Article-Organizer-and-Analyzer Academic-Article-Organizer-and-Analyzer Public

    This R script efficiently organizes and processes academic articles for citation analysis. It cleans file names, extracts and formats abstracts, and analyzes citations, streamlining the management …