– Owning the design, build, and maintenance of over 10 net new, and optimized over 20 Airflow DAGs /data models/ ETL, using SQL, Airflow, and Python, for the Customer Services and Safety team. The data models involve data table creation, complicated insert data logics, temp table clean-ups, data refresh scheduling, wait tasks, and data quality checks, etc.– Leverage my business domain knowledge, as well as my deep understanding of the data logic and quality, to collaborate with the leadership team on project management and priority settings– Monitor daily data backfills, on-call to fix data issues, investigate and response to challenging questions from stakeholders regarding the data quality issues– Work with the business stakeholders, to define metrics, and build Tableau and Mode reports to visualize and monitor their performances– Create and maintain high quality documentations for all the new and updated data processes

– Leverage SQL, BI reporting skills to incorporate multiple mobility data sources (web, call center, supply chain, finance team) to build reports, and perform data analysis and support across the company.– Apply quantitative analysis to detect opportunities, then use Python and R to provide productive suggestions to save cost and improve customer insurance claim experience– Primary machine learning models used are Logistic / Linear regression, A/B testing, Tree based models, NLP