Ted Cai Email & Phone Number | Top Skills: •Develop & Design data pipelines from intermedia or raw(log) tables, and enhance the data quality by data cleaning and data processing. •Extract data from multiple sources (Database, API Pipeline), dump into Tableau, and develop sustainable dashboards for business use cases. •Perform data analysis by using Pandas and NumPy libraries in Python, and provide strategic insights into the existing data metrics. • Predictive Modeling and Experimentation: Build Linear regression, Logistic regression, Random Forest, and Decision tree models based on the business use case. Implement A/B tests for product experimentation.

Ted Cai

Top Skills: •Develop & Design data pipelines from intermedia or raw(log) tables, and enhance the dat...
San Francisco Bay Area, San Francisco Bay Area, United States

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Ted Cai’s Email tcai@convoy.com

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Ted Cai’s Location San Francisco Bay Area, San Francisco Bay Area, United States

Ted Cai’s Current Industry Apple

Ted Cai’s Prior Industry Convoy | Facebook | California State University East Bay | Lusida Rubber Products

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Work Experience

Apple

Data Engineer

2023-10-01 00:00:00 - Present

Convoy

Business Intelligence Engineer, Marketplace Demand

2021-11-01 00:00:00 - 2022-11-01 00:00:00

Facebook

Data Analyst

2020-02-01 00:00:00 - 2021-01-01 00:00:00

California State University East Bay

Graduate Student Researcher

2018-08-01 00:00:00 - 2019-12-01 00:00:00

Lusida Rubber Products

Data Analyst

2017-01-01 00:00:00 - 2018-01-01 00:00:00

Skills

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FAQ About Ted Cai

Ted Cai is located at
San Francisco Bay Area, San Francisco Bay Area, United States

Ted Cai is a Top Skills: •Develop & Design data pipelines from intermedia or raw(log) tables, and enhance the data quality by data cleaning and data processing. •Extract data from multiple sources (Database, API Pipeline), dump into Tableau, and develop sustainable dashboards for business use cases. •Perform data analysis by using Pandas and NumPy libraries in Python, and provide strategic insights into the existing data metrics. • Predictive Modeling and Experimentation: Build Linear regression, Logistic regression, Random Forest, and Decision tree models based on the business use case. Implement A/B tests for product experimentation.