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.
- Name: Caiwen (Lisa) Li
- Email: [email protected]
- LinkedIn: linkedin.com/in/licaiwen/
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.
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Ph.D. in Data Science (Expected Graduation Year: 2025)
- Universiti Putra Malaysia, Kuala Lumpur, Malaysia
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M.S. in Statistics (2016)
- Hainan Normal University, Hainan, China
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B.S. in Applied Mathematics (2013)
- Hainan Normal University, Hainan, China
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C. Li (2016), "The securities market indicator for crash warning simulation optimization." Journal of System Simulation, Beijing, China.
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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.
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.
- Data Engineering with Google Cloud (Google Cloud, 2021)
- IBM Data Science (IBM, 2020)
- Advanced Google Analytics (Google, 2018)
- Google Partners (Google, 2018)
- 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)
- Conducting detailed summaries of articles on text mining techniques for recommendation systems.
- Developing a recommendation framework, including offline pipelines, feature engineering, and user segmentation.
- 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.
- 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.
- Utilizing Google and Adobe Analytics data to automate site performance reports.
- Coordinating campaign-specific findings and recommendations for digital media campaigns.
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.
Feel free to reach out to me at [email protected]. I am open to collaboration and discussion on data science, machine learning, and related topics.
Thank you for visiting my portfolio!