SUMMARY:

• 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

TECHNICAL SKILLS:

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

WORK EXPERIENCE:

Confidential, West Conshohocken, PA

Quantitative Data Analyst

Responsibilities:

• 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

Consultant

Responsibilities:

• 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

Intern

Responsibilities:

• 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

Responsibilities:

• 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

Responsibilities:

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