Work under the Credit Risk Management department of retail section at WeBank, China’s first and largest digital bank established by Tencent. Mainly contribute to the key product Weilidai, an unsecured loan service embedded in WeChat with more than 300 million clients.

- Undertook a large number of data-driven programs jointly with Risk/Marketing/R&D departments, for the use of building user personas, developing internet marketing campaigns, and improving products' user experience.- Proposed and implemented interactive risk dashboards(utilising Tableau), which are used for tracking business performance and supporting decision-making by the senior management team.

Meili Finance is a FinTech firm that focuses on providing online based consumption loans. My role in this company is to utilise SAS, SQL and Python to conduct data analysis for credit risk strategies. Core tasks include:- Writing Python programs to validate credit data and extract risk characteristics by interacting with MySQL as well as using statistical techniques;- Generating insights of fraud and default by analysing customer behaviours and overdue data using SAS;- Contributing to the development (implemented by Python) of credit scorecards and their monitoring models aimed at detecting fluctuations;- Producing and reporting weekly risk monitoring reports for post-lending management.

As a member of the Data Quality & Risk Systems (DQRS) team, worked on multiple projects to manage the data quality of the lending systems in Santander Bank UK by using SAS/SQL/Excel. This work was accomplished by collaborating closely with a number of associated departments, including the Risk, Sale and IT teams. Key responsibilities were:- Reconciled the ETL processes between multiple source systems and risk data repositories using SAS programming and SQL procedures;- Identified and investigated data issues as well as proposed corresponding solution by coordinating with the Risk and IT teams;- Represented the DQRS team to attend daily multi-team meetings for monitoring the progress of outstanding issues; - Designed and produced Management Information reports of lending systems on a monthly basis to assess the performance of internal users.

Undertook the research project - "An Implementation of Total Data Quality Management (TDQM) in the Banking Industry" sponsored by the Data Quality (DQ) department of Santander Bank UK. After having carried out comprehensive literature review and analysis of lending systems, a control model adopting the TDQM methodology was developed. This model was implemented in one of Santander’s key corporate lending systems to trace, measure and improve the data quality, enabling the DQ department to mitigate operational risks.

Research Project: "Robot Design for Train Seat Cleaning"This research project was derived from a collaboration between Cranfield University and Bombardier in finding the solutions to improve train maintenance services. Dedicating to three-month research, our multi-disciplinary team designed a robotic train-seat cleaner as well as implemented a prototype robot which was proved to significantly reduce the time and cost of train carriage cleaning. I mainly contributed to requirements analysis by investigating the client's needs as well as to robot movement design using Robot Operating System (ROS) programming.