• Designed and constructed data marts for the analytics team in Snowflake and Redshift, highly improved analytics cycle efficiency and reliability of reports• Led customer segmentation analysis and generate user stories based on their profiles; brought over 200 upsells for the RPA feature in 6 months• Conducted the churn deep dive analysis including A/B testing; reduced MH onboarding churn from 15% to 4%• Developed a churn prediction model in python, and provided the high-risk up-to-renew profiles report to the loyalty team to drive up the renewal rate

• Develop and manage custom analytic jobs with an emphasis on data mining, patter recognition, time-series analysis based on utility consumption data to help utility companies identify energy thefts and irregular meter conditions• Constantly develop new use cases and business intelligence visualizations tools based on stakeholders request • Integrate machine learning capabilities into browser widgets under .NET MVC framework, enabling deeper data interaction for end-users• Ensure optimal performance of daily analytic processes by optimizing SQL queries and ETL packages

Use Operation Optimizer software tool to find instances of theft, failed equipment, and energy efficiencycandidates; build new tools and algorithms corresponding to users’ requirements

• Develop prediction models to expand the investment strategies of the firm using advanced quantitative techniques such as machine learning, optimization, pattern recognition, and time series analysis;• Assess the profitability of proposed investment strategies by applying back-testing, rigorous statistics, and computational experiments on historical data;• Maintain and update sports information database, generate and visualize reports;• Perform sensitivity test for current investment strategies and provide optimized solutions on risk management

• Retrieved and cleaned industry level data from Guy Carpenter's database and created risk factors reports• Modified and tested a contagion factor model which significantly simplified the procedure of measuring the correlated insurance risk by lines of business for internal modeling • Optimized the contagion parameters between industry and individual companies via VBA and successfully predicted the insurance risk for most large insurance writers in US, such as AIG and Liberty Mutual • Contributed to editing 2014 Guy Carpenter’s Insurance Risk Benchmarks Research; the report on “Applying industry correlation metrics to the company level based on market share” would be published in December 2014

• Maintained internal pricing model to meet the CIRC regulatory standard• Performed profitability test and sensitivity test for insurance products• Collaborated with IT department to collate universal accounts balance and implement error analysis