Yangjie is available for hire
Hire YangjieYangjie Wu
Verified Expert in Product Management
Product Manager
Osaka, Osaka Prefecture, Japan
Toptal member since April 23, 2024
Bio
Yangjie is an experienced data product leader with a 9-year track record of delivering results through strategic consulting, machine learning modeling, AI application development, marketing experiments, and behavioral analytics. He is skilled in technical product management and data science. He has solved complex problems in companies such as Amazon, Coca-Cola, and Nike. With an eCommerce and information technology background, Yangjie continuously explores new dimensions of his role.
Project Highlights
AI Web Application Development
Spearheaded the design and development of enterprise AI web applications utilized by 100+ internal users.
Enterprise Data Product Development
Developed a comprehensive suite of data science applications from inception to delivery that provides services to 300,000+ merchants.
Data Science Practice for Mobile Marketing
Directed the design and development of a data science solution for mobile marketing targeting 5+ million monthly active users.
Expertise
- Business Intelligence (BI)
- Data Science
- Digital Transformation
- OpenAI GPT-4 API
- Python 3
- SQL
- Tableau
- Technical Product Management
Work Experience
Data Product Lead
2018 - 2024
Akachan Honpo Co.,Ltd.
- Led a cross-departmental project leveraging AI algorithms to drive personalized marketing campaigns, which resulted in a 10% increase in click-through rates and a 7% increase in conversion rates.
- Collaborated with the CMO and senior marketing officers on developing data-driven marketing strategies, which led to a 25% increase in marketing ROI.
- Integrated mobile application GA data with sales and marketing data to capture customer behavior in real time, resulting in a 3% uplift in customer engagement and a 5% increase in average order value.
- Developed a web crawler to analyze keyword search engine results and e-commerce marketplace data, processing more than five million item-level records daily.
- Developed a classification model to segment customers and products into focus groups for prioritization, leading to a 10% increase in targeted marketing accuracy and a 5% increase in customer satisfaction.
- Led a retail store Kaizen project to reduce checkout waiting time by 30% and mitigate inventory out-of-stock issues. This resulted in a 20% increase in customer satisfaction scores and a 25% decrease in stock-out incidents.
- Analyzed POS and supply chain data to identify opportunities and risks for seasonal products, resulting in a 15% reduction in excess inventory and a 5% increase in sell-through rates.
- Led business planning to improve overseas goods receipt lead time by 0.5 days, resulting in a 25% increase in overseas sales revenue and a 10% decrease in logistics costs.
Technical Product Manager
2019 - 2023
Amazon.com
- Led a team of eight engineers and data scientists in the development and launch of a machine learning-powered email marketing engine, which resulted in a 25% increase in user engagement and a 5% uplift in revenue.
- Managed six cross-department data products, with each catering to 100+ business users, automating email campaign workflow, improving demand forecast accuracy, and driving customized coupon delivery.
- Drove the development of a predictive AI tool that reduced customer churn by 10% and increased customer lifetime value by 5%. Led training sessions to democratize the use of AI products and increase product adoption by relevant business units.
- Owned product roadmap and managed product lifecycle; led weekly product performance review with stakeholders and managed monthly new version release cycle including prototyping, code review, alpha testing, beta testing, and go-to-market release.
Data Scientist
2019 - 2023
Amazon.com
- Headed in-house development of a hybrid large language model (LLM) to generate tailored marketing content.
- Leveraged Amazon SageMaker and Hugging Face, selected the foundation models, fine-tuned with customized training data, and optimized model performance through experimentation.
- Oversaw a team of data scientists and engineers developing scalable machine learning solutions that have helped 300,000+ merchants grow.
- Managed model development lifecycle and led monthly iterations on AI model retraining, feature engineering, and hyperparameter tuning.
- Led a team discussion to identify customer segments, developed AI algorithms for classifying merchants, conducted exploratory data analysis to unearth growth factors, created A/B tests, made feature trade-offs, and supervised product implementation.
- Designed architecture to ingest seller engagement data from a 3rd-party webinar application. Leveraged Python and AWS for pipeline automation and data wrangling. Led downstream impact analysis to align with seasonal business strategies.
- Created a daily tracking tool to monitor merchant account registration progress. Applied time series and cohort analysis for behavior insights. Developed business intelligence (BI) solutions to identify bottlenecks and enhance engagement.
Business Service Manager
2019 - 2019
Coca-Cola Company
- Spearheaded a data science product initiative to optimize vending machine assortment planning and boost sales forecast accuracy by 5%, resulting in a $1.5 million increase in annual revenue.
- Orchestrated a seamless on-premises-to-cloud data lake migration project, enabling real-time analysis of vending machine IoT data; achieved a 30% reduction in data processing time and a 15% improvement in data accessibility and operational efficiency.
- Oversaw a team of three data engineers from an IT vendor company, ensuring the successful delivery of cloud-based solutions tailored to the vending business. Achieved a 25% uplift in data processing capacity and a 40% reduction in infrastructure costs.
Business Intelligence Supervisor
2014 - 2017
Nike
- Architected and deployed BI tools to streamline value chain tracking for seven categories, driving a 10% increase in product demand coverage, a 5% boost in inventory turnover, and a 20% improvement in on-time shipment rates.
- Contributed to process automation. Engineered RPA tools to automate data processing workflows, effectively slashing planner workload by 50%. This initiative saved 20 hours per week per planner and reduced human error.
- Crafted and implemented 12 Tableau dashboards tailored to supply chain users, which improved planning accuracy by 5% and facilitated a 30% acceleration in cross-channel inventory transfers.
- Demonstrated team leadership. Directed a team of two product owners and two data professionals, providing strategic guidance, setting project roadmaps, and conducting regular audits of project deliverables.
Project History
AI Web Application Development
Spearheaded the design and development of enterprise AI web applications utilized by 100+ internal users.
I developed search applications and chatbots using LLMs and generative artificial intelligence (GAI) for eCommerce platforms. I also created web crawlers for Google search results and online shopping websites. I led UI enhancements, testing, automation of data APIs, and debugging tasks. Finally, I oversaw algorithm iterations and upgrades for scalability, customized AI application features for consumer needs, and balanced trade-offs for a cost-effective web application development cycle.
Enterprise Data Product Development
Developed a comprehensive suite of data science applications from inception to delivery that provides services to 300,000+ merchants.
Services include demand forecasting, dynamic pricing, and auto-customized marketing.
After aligning with the leadership team on a sales and marketing strategy, I designed business requirement specifications and tech architecture documents, as well as machine learning models to classify, prioritize, and engage merchants. To help merchants make decisions on listing, pricing, and inventory planning, I developed customized user functions. Also, I created marketing A/B tests to adjust user functions and UI experiences, developed a real-time BI dashboard to monitor the ecosystem, and upgraded machine learning algorithms tailored to business scenarios.
Finally, I automated the pipeline and flow among the suite of data applications, promoted data democratization, and provided training for business teams to achieve self-service.
After aligning with the leadership team on a sales and marketing strategy, I designed business requirement specifications and tech architecture documents, as well as machine learning models to classify, prioritize, and engage merchants. To help merchants make decisions on listing, pricing, and inventory planning, I developed customized user functions. Also, I created marketing A/B tests to adjust user functions and UI experiences, developed a real-time BI dashboard to monitor the ecosystem, and upgraded machine learning algorithms tailored to business scenarios.
Finally, I automated the pipeline and flow among the suite of data applications, promoted data democratization, and provided training for business teams to achieve self-service.
Data Science Practice for Mobile Marketing
Directed the design and development of a data science solution for mobile marketing targeting 5+ million monthly active users.
I led cross-team discussions on mobile marketing strategy based on time-series statistical observation and aligned the business target and goal metrics. My other responsibilities included:
• Conducting exploratory data analysis to identify key driver candidates and consolidating user journey scenarios.
• Designing architecture to process PB level data volume, constructing multi-layer data mart, and automating data flow from upstream Google Analytics log data to downstream aggregated visualization.
• Analyzing mobile user actions hourly, daily, weekly, and monthly and identifying features and signals that strongly correlate with click-through and conversion.
• Developing machine learning algorithms that auto-trigger coupon push notifications to mobile users showing purchase intention.
• Re-training and fine-tuning models to increase precision and recall.
• Conducting exploratory data analysis to identify key driver candidates and consolidating user journey scenarios.
• Designing architecture to process PB level data volume, constructing multi-layer data mart, and automating data flow from upstream Google Analytics log data to downstream aggregated visualization.
• Analyzing mobile user actions hourly, daily, weekly, and monthly and identifying features and signals that strongly correlate with click-through and conversion.
• Developing machine learning algorithms that auto-trigger coupon push notifications to mobile users showing purchase intention.
• Re-training and fine-tuning models to increase precision and recall.
Education
2013 - 2014
Master's Degree in Economics
University of British Columbia - Vancouver, BC, Canada
2007 - 2011
Bachelor's Degree in Economics
University of Victoria - Victoria, BC, Canada
Skills
Tools
Tableau, KNIME, GitHub, Spark SQL, Looker, Microsoft Access, R, Microsoft Power BI
Paradigms
Agile Project Management, Agile, Scrum
Platforms
Alteryx, Google Cloud Platform (GCP)
Other
Python 3, Amazon S3 (AWS S3), Redshift, SQL, Economics, Econometrics, Statistics, Mathematics, Technical Product Management, Business Intelligence (BI), Data Science, DBeaver, Product Management, Project Management, Business Analysis, Product Owner, Stakeholder Management, Backlog Management, Data Analytics, Amazon SageMaker, AWS Lambda, Visual Studio Code (VS Code), Google BigQuery, OpenAI GPT-4 API, Digital Transformation, Scrum Master, Business Services, Amazon EC2, Amazon DynamoDB, Amazon Athena, Hadoop, JavaScript, Large Language Models (LLMs), Robotic Process Automation (RPA), React, Data Product Manager, Natural Language Processing (NLP), Spark
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