Ruoying Li

Served as the leader of a compact data science team, specializing in an array of data analysis tasks, primarily focused on enhancing the user experience of an online sports application. My team's endeavors encompassed customer segmentation, extensive data analysis, chatbot development, and a detailed exploration of customer online behavior.

• Worked with stakeholders to develop quarterly roadmaps based on impact, effort and test coordinations.
• Analyzed large datasets to identify trends and patterns in customer behaviors.
• Discovered stories told by data to present information to scientists and business managers.
• Identified, measured and recommended improvement strategies for KPIs across business areas.
• Coached and mentored junior data scientists on data mining techniques.

Led data-driven projects to support major clients such as Ralph Lauren and Mercedes Benz

• Conducted comprehensive pre and post-campaign analysis to evaluate and enhance campaign design and effectiveness.
• Built and utilised propensity models, such as Lifecycle, Churn, and LTV (Life Time Value), to optimise targeting strategies and CRM.
• Developed and automated Tableau dashboards to simplify the reporting process.
• Responded to ad-hoc analysis requests from clients.

Provided data-driven insights to tackle various e-commerce business challenges and inform product decisions. Initiated and successfully led multiple projects from start to finish.

Project Highlights:

• Cost Optimisation on Digital Marketing for Rakuten Travel: Proposed and implemented strategies to improve the effectiveness of Rakuten Travel's listing ads, which helped increase the inflow, conversion rates, and ROI etc. Also automated the bidding process for these ads, which used to be done manually, and explored various attribution models to improve ROI. Additionally, monitored channel efficiency and provided reports to optimise budget allocation.
• New User Acquisition for Rakuten Travel: Developed solutions to acquire users with high lifetime value through similarity score modelling. Designed experiments to target specific groups of users for different services, such as dog-friendly hotels or ski resorts.
• A/B Test Analysis Tool: Built a tool for Rakuten Travel that computes and presents standard KPIs. The tool includes a Teradata dashboard where users can input test parameters, and then visualise the results.
• Rakuten ICHIBA Item Page Optimisation: Generated heat maps of key metrics such as CTR, CVR, bounce rate, and others for different item page components. Conducted post-test analysis and presented results to executive level managers.
• Coupon Experiment Design: Applied prediction models to determine the likelihood of conversion with coupons. Proposed an up-sell strategy and worked with business units for implementation.

Continued work in data analysis on genome data at NUS, with a focus on eye diseases.

• Similar analysis as my previous role in NUS with focus on eye disease.
• Assisted in image recognition and prediction of eye traits to aid in real-time diagnoses.
• Conducted image classification of eye disease data to support accurate diagnoses.

Main responsibility was to perform quality control and data cleaning on a large raw dataset, and run genome-wide association tests in genetic studies.

• Conducted model selection and evaluation for the association tests.
• Fitted linear or logistic regression models to the massive dataset to study the association between one trait and millions of genotypes on the human genome. Identified candidate genes with strong association for further investigation.
• Utilised the fitted model for prediction to identify potential patients with high risk of developing a disease