Verified Expert in Engineering
Ryan is a data-driven professional specializing in Bayesian statistics, machine learning, and real-time algorithm design. He brings years of interdisciplinary experience in statistics and machine learning with a sprinkle of business acumen from diverse industries in tech, advertising, real estate, finance, and insurance. Ryan has a fastidious ability to solve complex technical problems to reach desired results through novel ideas and rigorous approaches.
Visual Studio Code (VS Code), Jupyter Notebook, Python, Git
The most amazing...
...project I've developed is a fully distributed event-driven back-testing system that has led to my Sharpe 2.0+ quantitative market-neutral strategy.
Senior Machine Learning Engineer
- Led and contributed to Reddit's auto-bidding strategies. Worked on designing and implementing the core algorithm in a distributed, real-time environment.
- Incremental improvements in revenue of 2.5%, budget utilization of 12%, and 30% clicks.
- Provided technical leadership in algorithms and infrastructure behind the entire auto-bidding strategies.
- Took ownership of Maximize Clicks v2, Maximize Clicks v2.5 and Max Clicks Lagrangian.
- Performed rigorous experiment design and statistical validation throughout.
- Spearheaded distributed processing of over terabytes each day.
Duke University | Department of Statistics
- Utilized statistical and machine learning knowledge to develop new methodologies while improving the existing state-of-art ones.
- Conducted research aligned with recent field developments and literature. Implemented qualitative and quantitative analysis and data collection tools to achieve the assigned tasks within specified periods.
- Assisted the team in conducting intensive data analysis at MovieLens 25M datasets that explore people's movie rating behaviors from multiple lenses.
- Finalized and submitted research results to the group with recommendations on specific topics. Accomplished a seven-page write-up, supporting the team a step closer to the goal of publishing a paper.
- Spearheaded private equity fund operations, optimizing operational efficiency through systematized market operations and strategy development for a single-family value-add rental investment.
- Standardized business operations, value-add capital improvement projects, budget and timeline controls, trade coordination, and quality control assurance compliance with policies or regulations.
- Expanded business opportunities by directing a total asset of over $5 million, capitalizing on management and excellent communication skills to convey a consistent annual equity return of more than 15%.
- Bolstered operations, revenue generation, and client base expansion by instituting innovative portfolio management strategies for over 33 units across Philadelphia Metro.
- Executed comprehensive property management, incorporating best practices in tenant screening, repair and maintenance, cost control, rent collection, dispute handling, and capital improvement to meet optimal equity and internal rate returns.
- Boosted strategic leadership and communication among stakeholders and cross-functional teams, instilling the company vision to influence business transformation and meet objectives.
Senior Data Scientist
- Developed the company's first customer segmentation model about life insurance purchasers' key life events and behavior drivers, utilizing extensive statistics modeling and pulling data from a large volume of datasets from various sources.
- Achieved an average of 1.6 times of target segment lifts, reducing the client acquisition cost and improving conversation rate to optimize the overall marketing profit and loss (P&L).
- Amplified the AUC metric by over 8% by introducing nonlinearity with additional critical behavior features into the prospect-predicting model.
- Established rich interactive visualizations through data interpretation and analysis to integrate multiple data sources to support performance analysis, agency and producer ranking and awards, and internal marketing strategy.
- Evaluated data collection processes for various business reports, utilizing multiple datasets to develop visual displays of solutions. Communicated data analysis results in written and verbal form for a more effective presentation.
- Strategized business intelligence solutions by updating the latest information technology applications. Automated over 80% of department internal ad-hoc reports using Python, Tableau, Excel, and VBA.
Operation Research Consultant
Gemological Institute of America
- Supervised more than three professionals in a supply chain optimization project to streamline the internal quality control logistic system.
- Theorized the logistics system using linear programming and proposed a route for production implementation. Provided a full-size demo on Python and Django frameworks focused on online learning.
- Formulated an operational strategy, mapped a value chain, and conducted quantitative research for prospective institute models.
Equity Investment Web App
Distributed Event-driven Backtesting System
Manhattan College Business Analytics Competition | First Placehttps://manhattan.edu/news/archive/2015/05/first-annual-business-analytics-conference-and-competition-explores-art-and-science-decision
Python, SQL, Scala, Excel VBA, Go, Java
Pandas, NumPy, Scikit-learn, PySpark
Git, Tableau, BigQuery, GitHub
Object-oriented Programming (OOP), Unit Testing, Business Intelligence (BI), Distributed Computing, Linear Programming, Data Science, ETL, Event-driven Programming, Real-time Systems, Dynamic Programming, MapReduce
Jupyter Notebook, Oracle, Docker, Visual Studio Code (VS Code), Amazon Web Services (AWS)
PostgreSQL, Data Pipelines, MySQL, MongoDB
Operations Research, Mathematics, Statistics, Big Data, Analytics, Algorithms, Linear Algebra, Partial Differential Equations, Principal Component Analysis (PCA), Optimization, Stochastic Gradient Descent (SGD), Machine Learning, Bayesian Statistics, Recommendation Systems, Computational Advertising, Research, Dashboards, Asset Management, Equity Investment, Asset Valuation, Private Equity, Wealth Management, Customer Segmentation, Excel 365, Data Visualization, Data Cleaning, Statistical Learning, Data Analytics, Data Engineering, Financial Engineering, Competitor Analysis & Profiling, Time Series Analysis, Distributed Systems, Software Engineering, Quantitative Analysis, Numerical Analysis, Algorithmic Trading, Statistical Modeling, Reinforcement Learning, Bayesian Inference & Modeling, Experimental Design, Real-time Streaming, Real-time Bidding (RTB), Graph Theory, Leadership, Property Management, Cross-selling, Upselling, Dash, Data Scraping, Streamlit, APIs, Ads, Advertising, Back-end, Causal Inference, Natural Language Processing (NLP), Signal Processing, Back-end Development, Game Development, Artificial Intelligence (AI), GPT, Generative Pre-trained Transformers (GPT)
Hadoop, Spark, Django, WebApp, Flask
Master's Degree in Statistical Science
Duke University - Durham, NC, United States
Bachelor's Degree in Business Analytics
Pace University - New York, NY, United States
Reinforcement Learning Specialization
Fundamentals of Computing Specialization
Mathematics for Machine Learning Specialization