About Me
I'm passionate about finding the insights in data, using techniques of statistics and machine learning to grow the business and integrating artificial intelligence solutions into the application.
I'm skilled at programming (SQL, Python...
Skills
Data & Analytics
Software Engineering
Database
Web Development
Development Tools
Programming Language
Software Testing
Operating System
Others
Graphic Design
Portfolio Projects
Company
End-to-end A/B testing process
Role
Data Scientist
Description
- Design, data modeling, execution and statistical analysis.
- Work directly with business owners and IT to plan, execute, and analyze all A/B & multivariate tests.
- Develop and document testing processes and policies to further increase the quality and rigor.
- Provide analysis of each experiment to understand the impact on marketing campaigns or product roadmaps.
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Data Science Python SQL A/B TestingCompany
Database design and ETL development
Description
- Analyse and collect unstructured data.
- Database design and data modeling
- Implement ETL and automate the integration process.
- Be responsible for the availability and the reliability of data needs of other departments
- Create and improve tools for data science and data analytics team
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Skills
Java (All Versions) Python Linux Big Data SQL Database Design Database Modeling Database ProgrammingTools
Eclipse Jupyter Notebook GithubCompany
Churn Classification
Role
Data Scientist
Description
- Write SQL and do the visualization to understand the user's behaviors and interests.
- Define a target metric to measure user engagement.
- Build a Machine Learning model to classify engaged and unengaged users.
- Setup and analyse A/B Testing to validate the model.
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Azure Python Jupyter Notebook MetabaseCompany
Text Classification
Description
- Analyse the data and create new features
- Transform text data into Term Frequency - Inverse Document Frequency, select the best feature with f_classif and fit the transformed data to Bayesian algorithm
- Transform text data into Word Embedding, select the best feature with f_classif and fit the transformed data to Bayesian algorithm
- Word Embedding + Bayes improves 8?curacy from 86% (baseline) to 94% Meanwhile TF-IDF + Bayes improve 5?curacy from 86% to 91%
- Github: https://github.com/diem-ai/text-classification
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Tools
Python Jupyter Notebook