Yutong Yin
Falls Church,VA
Summary
Results-driven Data Scientist with a Ph.D. in Research Methodology and dual Master’s degrees in Statistics and Computer Science. Demonstrates expertise in data analysis, visualization, and statistical modeling, utilizing tools such as R, Python, SQL, SAS, Tableau, and Power BI. Successfully identifies patterns within large datasets while developing predictive models and automating reporting processes to enhance organizational efficiency. Strong collaborator with proven problem-solving skills, capable of presenting actionable insights and leading cross-departmental projects.
Overview
18
18
years of professional experience
1
1
Certification
Work History
Data Analyst and Statistician II
USPS
01.2020 - Current
- Conduct extensive analysis of budget activities and financial performance metrics, utilizing statistical analysis for decision support
- Create and maintain reports using data analytics tool(e.g., Power BI) to track field budget performance, ensuring accuracy and actionable insights
- Lead the development and automation of methodologies, improving financial data accuracy using data science tools (ETL, R/Python)
Quantitative Modeler II
Fannie Mae
01.2018 - 01.2020
- Applied data science and analytics in housing market forecasting, leveraging data visualization tools for financial reporting and trend identification
- Facilitated cross-departmental discussions and workshops to interpret complex model results for informed decision-making
Principal Quantitative Analyst
Capital One
01.2017 - 01.2018
- Work on economic capital planning initiatives through advanced statistical modeling and scenario analysis to forecast financial reserves and assess risk
- Developing and automating data processes and financial reports
Data Scientist, Big Data Group
K12 Inc.
01.2015 - 01.2016
- Utilized SQL for extracting, cleaning, and manipulating large datasets for streamlined data integration and analysis
- Analyzed relationships within large datasets using data science methodologies to identify actionable patterns for operational decision-making
- Designed and implemented advanced statistical and machine learning models to automate data predications and improve model performance
- Leveraged data visualization tools, including Tableau and R, to create dashboards for internal reporting and decision support
- Communicated complex analytical findings to cross-departmental teams, driving initiatives from data analysis to deployment and application
Psychometrician, Employment Testing
Edison Electric Institute
01.2007 - 01.2015
- Conducted psychometric analysis using descriptive and inferential statistics to define job roles and assess performance metrics
- Built predictive models using statistical techniques to evaluate and enhance test validity and reliability
- Spearheaded the development of data collection processes with an emphasis on automation and data quality assurance using SAS and R
- Presented data-driven insights and research findings to diverse audiences, facilitating informed decision-making across organizational levels
Education
PhD - Research Methodology
University of Pittsburgh
01.2007
MA - Statistics
University of Pittsburgh
01.2006
MS - Computer Science and Engineering
University of Connecticut
01.2003
Skills
- Programming: Python, R, SQL
- Machine Learning: TensorFlow, Spark, Scikit-learn
- Data Visualization: Tableau, Power BI, Matplotlib, Seaborn
- Big Data: Hadoop, Spark
- Statistics: Regression, Classification, Clustering
- Databases: SQL, NoSQL
- Cloud Computing: AWS, Azure, Google Cloud
Certification
- Data Scientist Certification, University of California, Berkeley (ongoing)
Background core courses
- Data Scientist and Analytics: Advanced coursework in databases, machine learning using Python, data visualization, big data analytics, and deep learning (e.g., Spark)
- Statistics and Mathematics: Comprehensive training in applied probability theory, survival analysis, Bayesian statistics, time series analysis, multivariate statistics, and statistical modeling.
- Computer Science: Expertise in advanced database systems, software performance engineering, distributed systems, and computer security, providing a foundation for complex data integration, analysis, and secure data management.
- Educational Measurement: Specialized knowledge in research methodology, psychometric analysis, item response theory, and computer applications for testing and assessment.
Timeline
Data Analyst and Statistician II
USPS
01.2020 - Current
Quantitative Modeler II
Fannie Mae
01.2018 - 01.2020
Principal Quantitative Analyst
Capital One
01.2017 - 01.2018
Data Scientist, Big Data Group
K12 Inc.
01.2015 - 01.2016
Psychometrician, Employment Testing
Edison Electric Institute
01.2007 - 01.2015
PhD - Research Methodology
University of Pittsburgh
MA - Statistics
University of Pittsburgh
MS - Computer Science and Engineering
University of Connecticut
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