• Leverage knowledge of programming, mathematics and computer science to transform the way the company does business.• Translate business opportunities into data-driven machine learning, Big Data, and modeling solutions that revamp processes or produce data products.• Develop and collect data for ad hoc and statistical analyses.• Identify methods that allow continuous and automated statistical testing to enhance the predictability of deployed models.• Maintain relationships between business-area clients, business intelligence and IT so all teams are aligned to meet team objectives.• Work with Project Managers to develop detailed project timelines.• Summarize and present conclusions and solutions.• Communicate complex analyses clearly to all audiences.

• Collect data for ad-hoc and statistical analysis.• Clean data in preparation for analysis and modeling.• Perform statistical summaries and tests for relevant business questions.• Develop predictive statistical, behavioral or other models.• Perform statistical testing to enhance the predictability of deployed models.• Deploy applicable models for business use.• Summarize conclusions and solutions for presentations.• Develop strong relationships with subject matter experts.

• Identified factors that best predict an impending life event and the probability that a member will contact the USAA. • Performed data preprocessing include: principal component analysis, missing value imputation, and anomaly detection.• Clustered members based on their behavioral and demographic attributes and applied supervised and unsupervised methods to evaluate the clusters. • Built supervised machine learning models to predict how new members in those clusters will behave.

• Automated the data scraping from members’ ACH files and designed MySQL database to store the data.• Identified key demographics of customers who are repeatedly making payments at other financial institutions.• Designed operational models that predict the likelihood of a customer use another financial institution and use bill payment service based on behavioral, geographic, and demographic data. .

• Teams working to explore 2.3 million transaction data provided by the company, cleaned datasheet and restructured data into a more practical data by using SPSS Modeler. • Developed models by using transaction data and customer demographic data that enable company to identify attributes and behaviors of customers that could improve customer average order value (AOV).• Exposed to data mining and applied statistics, including decision tree, Bayesian network, and general linear model.

• Analyzed industry economic condition, investigated the clients’ assets and financial background. • Researched current and past transactions to develop investment guidelines and framework for evaluating future investments within the emerging and developing markets space in Asia-Pacific.• Assisted associate in screening, background research, and preliminary due diligence on potential new investments.• Evaluated and Translated investment analysis reports from English to Chinese for Chinese investors to make investment decisions.