- Accomplished a 32% reduction in triage workload by developing and implementing an ML model with 96.2% precision rate in product issues classification, utilizing TFIDF for data preprocessing and SVM for classification, while integrating regular validation metrics and anomaly detection algorithms for continuous performance enhancement. - Accomplished a 97.8% typo correction rate in product issue notes input by time-constrained product testers, by developing and deploying an NLP model. Developed innovative approach utilizing historical issue notes to create a customized correction dictionary and implemented correction based on edit distance and word frequency to enhance accuracy of the issue triaging.- Achieved a 27% increase in accuracy rate for weather-related product issues following comprehensive causal analysis. Identified outdated algorithms as the primary root cause and collaborated cross-functionally to introduce a new issue tag, resulting in enhanced accuracy across all events. - Enhanced triage accuracy from 92% to 98% by developing and implementing a cross-validation model, leveraging Natural Language Processing and LLM Foundation model to identify similar product issues and highlight suspicious ones for further review. - Designed and implemented data engineering solutions to integrate disparate data sources into automated ETL pipelines for comprehensive product performance metrics. Created hourly refreshed Tableau Dashboards that served as essential references for over 100 individuals across 8 teams to track product progress and issue resolution.

- Achieved a 35% increase in storage space utilization efficiency by fully automating the product slotting process for business clients. Utilized Python and SQL to implement supervised learning algorithms (logistic regression, linear regression, SVM) for predicting product popularity, identifying seasonal sales patterns, and optimizing storage allocation.- Reduced quoting turnaround time from 14 days to 2 days by integrating data models from multiple departments. Continuously enhanced operational efficiency through the deployment of an automated end-to-end solution, streamlining the quoting process and implementing new features.- Conducted extensive analysis of business clients' warehouse data to identify key performance measures and insights, informing the design of robotic automation solutions and optimizing warehouse processes using Python and SQL. Visualized data in Tableau Dashboard enabling clients and other teams to answer business questions independently.- Collaborated with R&D team on a comprehensive project encompassing product analysis, metrics design, causal analysis, and conducted descriptive analysis to derive business insights and presented to R&D leaders bi-weekly. 159-page final deliverable was accomplished and resulted in the implementation of recommended product features into production.

- Analyze data for warehouse design, including ASRS system configuration, Warehouse Zones design, SKU slotting, operation schedule design, and capacity planning. Visualize data with Python/Tableau/Excel, develop slides and other deliverables, present results to client. Completed more than 150 data analysis projects with more than 50MM total sales value successfully. 
- Develop Python Scripts to conduct descriptive analytics on clients’ Order Data, SKU Data and Inventory Data, tracks key performance indicators to configure Perfect Pick and Sure Sort Robotics Automation solutions. Created prescriptive analytics algorithm with python, including advanced product storing algorithm, SKU slotting algorithm, items packaging algorithm, Order container routing algorithm, Seasonality Analysis algorithm etc. - Conduct market research, support developing pricing strategy, service contract strategy, discount tiers for clients, service bases locations planning, etc. Conduct competitive analysis, make suggestions for future product development plan.- Developed tools with Python/Excel to support Sales/Marketing/Service Department, including Customized Configuration Tool, ROM Pricing Calculator, ROI Calculator, Throughput/Acceptance Test data visualization tools, etc. Maintain and update internal tools regularly. 
- Conduct phone screening, on-site interview, and tech interview on candidates. Recruit, Train and supervise junior analytics staff.

- Data analysis: Develop python/SQL scripts to parse clickstream data and calculate statistics. Clustering users by demographic information, devices used, and viewing habits, etc. Develop models, including logistic regression, linear regression, locally weighted regression, naïve bayes to identify correlations, patterns, insights and develop strategies for clients. Prepared reports and deliverables. Developed slides for client meeting biweekly. - Web crawler: Develop python web crawler program to collect Netflix show info, including Show ID, year, time length, description, genres, etc. Develop advanced web crawler to automate web browser interaction, creating AT&T direct TV database of full domestic client address list.- Automate and optimize processes of collecting, cleaning clickstream data with Python regularly. Updated databases automatically with SQL, MongoDB (NoSQL), including Netflix Database, Wikipedia video & media content Databases, User-Agent Databases.