Ryan Tang, Statistics Developer in Phoenixville, PA, United States
Ryan Tang

Statistics Developer in Phoenixville, PA, United States

Member since January 21, 2022
Ryan is an accomplished statistician with years of progressive experience in data science, specializing in machine learning, statistics, and big data analytics. He has an exceptional ability to solve complex technical problems using statistics and algorithms and demonstrates excellent initiative to perform duties independently. Ryan has vast experience in multiple industries. This interdisciplinarity allows him to be ingenious and innovative.
Ryan is now available for hire




Phoenixville, PA, United States



Preferred Environment

VS Code, Jupyter Notebook, Python, Git

The most amazing...

...project I've developed is a fully distributed event-driven backtesting system that has led to my Sharpe 2.0+ quantitative market-neutral strategy.


  • Machine Learning Engineer

    2022 - PRESENT
    Reddit, Inc.
    • Developed, designed, and deployed the first auto-bidding product for Reddit.
    • Achieved an overall 30% budget efficiency for eligible campaigns.
    • Designed and developed multiple improvements to the algorithm and achieved millions of revenue gains.
    Technologies: Data Science, Distributed Systems, Software Engineering, Go, Scala, Python, Java, Spark, BigQuery, ETL, Mathematics, Quantitative Analysis, Numerical Analysis, Algorithms, Back-end Development, Machine Learning
  • Research Scientist

    2021 - 2022
    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.
    Technologies: Python, Algorithms, Machine Learning, Statistics, Bayesian Statistics, Recommendation Systems, Computational Advertising, Research, Mathematics, PostgreSQL, Data Science, NumPy, Pandas, SQL, Data Engineering, Quantitative Analysis, Distributed Systems, ETL, Numerical Analysis, Ads, Advertising, GitHub, Git, Data Analytics, Statistical Learning, Statistical Modeling
  • Principal

    2015 - 2021
    Ridge Equities
    • 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.
    Technologies: Python, Dashboards, Statistics, Machine Learning, Business Intelligence (BI), Asset Management, Equity Investment, Asset Valuation, Leadership, Property Management, Private Equity, Wealth Management, PostgreSQL, Dash, Quantitative Analysis, Algorithms, WebApp, Flask, Back-end Development, Data Science, Git, GitHub, Data Analytics, Statistical Learning, Statistical Modeling, Back-end, Pandas, NumPy, SQL, Data Engineering
  • Senior Data Scientist

    2016 - 2017
    Guardian Insurance
    • 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.
    Technologies: Python, Analytics, Business Intelligence (BI), Hadoop, Spark, Machine Learning, Customer Segmentation, Cross-selling, Upselling, Statistics, PostgreSQL, Oracle, PySpark, MapReduce, Data Pipelines, Distributed Computing, NumPy, Pandas, Data Engineering, SQL, Data Science, Distributed Systems, Software Engineering, BigQuery, ETL, Tableau, Quantitative Analysis, Numerical Analysis, Algorithms, AWS, Git, GitHub, Back-end, Amazon Web Services (AWS), Docker, Data Analytics, Statistical Learning, Statistical Modeling, MySQL, MongoDB
  • Business Analyst

    2014 - 2016
    Guardian Insurance
    • 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.
    Technologies: Python, Statistics, Analytics, Business Intelligence (BI), Dashboards, Excel 365, Excel VBA, Tableau, PostgreSQL, Oracle, Data Visualization, Data Pipelines, Data Cleaning, Data Scraping, SQL, Data Engineering, NumPy, Pandas, Data Science, Quantitative Analysis, ETL, Algorithms, Numerical Analysis, Git, GitHub, Back-end, Data Analytics, Statistical Learning, Statistical Modeling
  • Operation Research Consultant

    2015 - 2015
    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.
    Technologies: Python, Django, Operations Research, Linear Programming, Optimization, Research, Data Science, Data Engineering, SQL, MySQL, NumPy, Pandas, Machine Learning, Quantitative Analysis, Numerical Analysis, Algorithms, Back-end, Back-end Development, Git, GitHub, Data Analytics, Statistical Learning, Statistical Modeling


  • Equity Investment Web App

    This is a Streamlit-powered data application for value investment research on stocks. The ultimate purpose of this app is to provide comprehensive fundamental data to make informed investment decisions. It consists of the competitor analysis, debt and leverage analysis, operational efficiency, return on investment (ROI), return on equity (ROE), and cash flow.

  • Distributed Event-driven Backtesting System

    A pythonic event-driven backtesting system was used to analyze my quantitative strategies. It has a component that handles slippage and order executions, a portfolio manager that rebalances between multiple concurrent strategies, and an extensive backtesting analytics component for in-depth research.

  • Manhattan College Business Analytics Competition | First Place

    The events featured industry leaders and included an exciting opportunity for undergraduate students studying business analytics or related fields to test their knowledge and develop their skills. Competing students engaged in the “art and science” of decision-making while practicing their ability to draw business insights through comprehensive analyses of data in creative ways. My team and I, as a team lead, won first place in this competition.


  • Languages

    Python, SQL, Excel VBA, Go, Scala, Java
  • Libraries/APIs

    Pandas, NumPy, PySpark
  • Tools

    VS Code, Git, Tableau, GitHub, BigQuery
  • Paradigms

    Object-oriented Programming (OOP), Unit Testing, Business Intelligence (BI), Data Science, ETL, Dynamic Programming, MapReduce, Linear Programming, Event-driven Programming, Distributed Computing
  • Platforms

    Jupyter Notebook, Oracle, Amazon Web Services (AWS), Docker
  • Storage

    PostgreSQL, Data Pipelines, MySQL, MongoDB
  • Other

    Operations Research, Mathematics, Statistics, Big Data, Analytics, Algorithms, Linear Algebra, Partial Differential Equations, Principal Component Analysis (PCA), Optimization, Stochastic Gradient Descent, 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, Quantitative Analysis, Numerical Analysis, Algorithmic Trading, Statistical Modeling, Graph Theory, Leadership, Property Management, Cross-selling, Upselling, Dash, Data Scraping, Streamlit, Time Series Analysis, Distributed Systems, APIs, Ads, Advertising, Natural Language Processing (NLP), Signal Processing, Software Engineering, Back-end Development, AWS, Back-end, Game Development, Reinforcement Learning, Artificial Intelligence (AI)
  • Frameworks

    Hadoop, Spark, Django, WebApp, Flask


  • Master's Degree in Statistical Science
    2022 - 2022
    Duke Univesrity - Durham, NC
  • Bachelor's Degree in Business Analytics
    2011 - 2015
    Pace University - New York, NY, United States


  • Reinforcement Learning Specialization
  • Fundamentals of Computing Specialization
  • Mathematics for Machine Learning Specialization

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