-  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.

- 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 

- 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.

- 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