Atlanta Metropolitan Area
As a committed business data professional versed in unwinding complex datasets and building constructive data products, I rise to challenges with a versatile analytical toolbox under my belt, including Data Engineering, Business Intelligence, and Data Science. Having thrived from established to startup environments and expansive experience in retail, finance, risk, online marketing, and operations areas, I am a vision-driven pragmatist, a collaborative self-starter, and a principled innovator. I always enjoy serving a meaningful purpose, exploring different paths, and connecting to others through education, inspiration, and support. Known for my relentless persistence, empathetic openness, and strong work ethic, I grow in overcoming setbacks, developing empowering stories, and delivering impactful data capabilities. Besides work, I am a curious and passionate lifelong learner with a multidisciplinary background across humanities/cross-cultural studies, business, and technology. You’ll most likely find me at church and community fellowship, out of concert halls or the woods, or simply in a quiet corner conversing with the great minds or beading the next dream. - Programming languages and Technical tools: SQL, Python, Tableau, Google Cloud Platform (BigQuery, Google Cloud Storage, Vertex AI Workbench), AWS, shell/bash, Jira, Confluence, Github, Excel, Hadoop, Spark, SPSS, Minitab, HTML/JS/CSS, Java - Analytical skills: Data Management and Pipelining, Business Intelligence Engineering, Data Visualization and Dashboard Reporting, Automation, Data Cleaning and Manipulation, Machine Learning Modelling fundamentals, Statistical Analysis, Data Mining, Descriptive Analytics, Predictive Analytics, Prescriptive Analytics
Project: Analyzing Impact of Coronavirus News on the U.S. Stock Market (modeling techniques: Text Mining, Sentiment Analysis, Multivariate Regression & Statistical Data Analysis etc.)
• Extracted and wrangled 5+ various types of cryptocurrency datasets (e.g. tickers, historical & real-time transactions, news, block on-chain data, wallet information) from exchanges and third-party providers using Python REST APIs, SQL & Python data manipulation packages (e.g. NumPy, Pandas) for data product support • Analyzed and visualized daily market trends & patterns in custom Tableau dashboards with 7 technical monitors calculated and monitored over time for providing investors & traders with market insights • Researched, designed and implemented quantitative models for trading strategies in Python based on 11 KPIs with performance backtesting and parameter tuning, achieving 28.46% return over backtesting period using best model
• Interviewed client frontline managers and operational staff on-site for understanding top concerns, collected and defined key business requirements, set feasible project goals based on case study and research, and managed expectations and maintained relationships through regular check-ins and effective communication • Outlined entire service handling operational procedure through process flowcharts, and identified potential levers in the underlying data generation process • Processed, integrated and cleansed 3M+ records of service requests over the past 6 years on different aspects (e.g. call intake, work order, customer survey) from multiple MIS sources using Hadoop, Python & Excel, mapping fields & entries correctly and transforming raw data into a unified source of storage in its appropriate form • Captured likely service fulfillment delay cases with 88% accuracy in Python modeling, boosting customer satisfaction rate through appropriate escalation and expedited handling accordingly • Predicted upcoming weekly volume of specific request topic by regions for better workload responses and service resource planning, utilizing geocoding techniques and optimal XGBoost model through machine learning training & evaluation in Spark and AWS; reduced RMSE metric by 65% against benchmark with external data sources synthesized • Initiated interactive Tableau dashboarding solutions to track 3 key performance metrics on 6 workflow aspects for proactive reporting and root cause analysis; provided self-service capabilities for client to dynamically detect anomalies and examine impacts of new changes on operations optimization • Managed team to communicate data-driven findings and solutions to client with documentation weekly, and trained end-users onsite (To get a rough sense of business intelligence part of the work products, please navigate to the following link for a short demo video.)
• Facilitated 3 concurrent projects focused on digitalization and operational process transformation for largest multinational insurance and trust companies, collaborating with vendors and across 4+ functional teams • Strategized redesign of client’s core information systems in 15% less overhead by conducting market research and case studies for best big data & AI practices in industry • Presented competitive landscape overview and solution gap analysis reports to clients & stakeholders at different levels, by consolidating, analyzing & interpreting data of various sources in SQL & Excel and conveying important recommendations through engaging presentations in PowerPoint • Profiled target high-net-worth customers with expected 25% business expansion based on segmentation analysis on consolidated market data in SQL & Python • Coordinated with clients & vendors on managing requirements & tasks during the process through documentations etc.; Visualized & monitored project plans, statuses, change controls and RAIDs constantly in Power BI Reporting to support project management
• Fulfilled 7 deals by extracting U.S. and Chinese asset-backed security data from internal MySQL databases, formulating complex waterfall models for asset and liability cash flow analyses, and manipulating large spreadsheets with 60+ columns • Automated Monte Carlo simulation for loss prediction and credit rating modeling for company’s 10+ structured finance products in Excel VBA with scenario analysis in Python; reported to senior management with weekly reviews of risk evaluation • Improved efficiency of proprietary built-in parameter searching algorithm for capital structure optimization by 30% in Java