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Quantitative Data Analyst Resume

West Conshohocken, PA


  • Analytical professional in Financial Industry (passed CFA Level 1) with backgrounds in Financial Engineering and Statistics
  • Extensive experience in quantitative analysis, statistical modeling and feature selection/engineering
  • Proficiency in statistical software and programming languages including SAS, R, SQL, Python, VBA, etc.
  • Team player, open - minded, fast learner, detail-oriented, excellent English verbal and written communication skills
  • Machine Learning
  • Statistical Modeling/Validation
  • Data Wrangling
  • Data Visualization
  • R/Python
  • SQL/Database


R (R Studio): RODBC, dplyr, tidyr, ggplot2, shiny, rmarkdown, forecast, caret, etc.

Python (IPython Notebook, Spyder): NumPy, pandas, SciPy, Scikit-learn, GraphLab, etc.

SAS: PROC and DATA steps to for data extraction/cleansing/processing, visualization and modeling, etc.

Excel: advanced formulas, pivot table, conditional formatting, data validation, table manipulation, chart creation, ODBC, etc.

VBA: controls, macros, UserForm design, Module, recordset, ODBC, excel to powerpoint/outlook, etc.

SQL: stored procedures; design of Entity-Relationship Diagrams and Relational Schemas; table manipulation (select, format, summarize, segment, join, subquery); implementation in SAS, R and Python

UNIX: basic commands; file/directory management; process management; vi editing; shell scripting

C#: application development

Other Skills: MySQL, T-SQL, NoSQL, Teradata, SQL Server 2008 R2; MATLAB; Microsoft Office Suite Word, PowerPoint, Outlook; Adobe Photoshop; Java


Confidential, West Conshohocken, PA

Quantitative Data Analyst


  • Developed and implemented a US equity algorithmic trading strategy
  • Developed a proprietary database compiling data of various sources for research on stocks of interest
  • Fundamental analysis on target stocks to discover statistical arbitrage
  • Daily operation/maintenance of the trading algorithm and the database
  • Daily reporting of portfolio returns and relevant risk statistics
  • Researching and reporting on new target stocks
  • Quantitative and statistical analysis on investments in external managers (R, Python, Excel and VBA)
  • Assessing the performance and risk of managers invested
  • Top-down and bottom-up risk management on marketable and non-marketable portfolios
  • Conducting statistical analysis on managers’ return stream to identify potential risk and evaluate factor exposures
  • Performing ad hoc studies for PE/VC, real assets and hedge fund investment strategies of interest

Confidential, New York, NY



  • Developed Excel Reporting Interface for Credit/Price/Interest Rate/Liquidity KRI (VBA)
  • Developed architecture for data extraction, data cleansing and data reconciliation for risk data (Access, R, T-SQL)
  • Streamlined and transforming business data & process into practical technological solutions
  • Performed analysis on related KRI and generated automation report and visualization
  • Risk Data Aggregation (RDA, Basel III - BCBS 239)
  • Dialogued with Business and Technology teams on risk data and KRI report requirements
  • Created and reviewed the RDA documentation including: Business Data Requirement, Data Dictionary, Data Quality Rules, End-to-End Mapping, Critical Data Element, RACI Framework, Process and Control Flow and System Flow
  • Created templates for monthly risk data collection and consolidation from stakeholders
  • KRI-RDA Project Management
  • Kept tracking the status of RDA deliverables with each line of business responsible
  • Identified project risks, issues and dependencies and adjusting project plan and timeline accordingly
  • Prepared bi-weekly project update presentation for the board of Managing Directors and General Managers
  • Worked as liaison of several teams to unify Operation, Legal & Compliance, Risk Management and Technology in the KRI-RDA project to meet regulatory requirements (OCC)

Confidential, New York, NY



  • Performed data management including data cleansing, data reconciliation and validation on cost-of-living data collected from UN duty stations globally
  • Maintained databases for cost-of-living data and worked as liaison of the statistician team and data collection team
  • Performed analysis to detect outliers to study and examine cost-of-living data with skewed distribution

Confidential, Colchester, CT

Data Engineer Intern


  • Developed a new robust and automatic monthly forecasting system (predictive modeling) in R for 10,000+ individual items
  • Data extraction from MySQL database; data reconciliation and data validation
  • Data cleansing on the monthly sale history data for the following modeling and model evaluation process
  • Outliers adjustment using linear regression and seasonality detection using ANOVA analysis
  • Application of 14 different predictive models on the time-series data to make predictions for future sale
  • Model evaluation and validation; model selection based on forecasting accuracy on the test data
  • Data visualization for the forecasting from the selected model with outlier indication and seasonality detection
  • Web application interface design with input parameter adjustment and output table and figure display
  • Produced and documented methodologies to evaluate forecasting error
  • Performed quantitative analysis and data visualization on a flash sale event to evaluation the performance of the event

Confidential, Storrs, CT

Research/Teaching Assistant


  • Extensive experience in laboratory work, literature search, independent project design and management, and troubleshooting
  • Led courses and discussion sessions for undergraduate students

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