Statistical Modeling – Derived hypotheses on how to increase click through rates and revenue on search page. Built models to identify significant predictors clicks and adjusted weights in search algorithm accordingly. Common techniques included support vector machines (SVM), random forests, naïve Bayes classifiers, k-means clustering and logistic regression.A/B Testing – Assessed the feasibility and performance of new features based on user behavior. Built infrastructures to simulate data, designed and implemented A/B tests, and reported effects of treatments.Natural Language Processing – Summarized millions of user generated reviews into a list of clean, meaningful phrases for each company. Recommended additional search terms for job seekers using collaborative filtering.Big Data Extraction and Manipulation – Wrote complex Pig and SQL queries.

Social Network Analysis – Determined the influence and extent of collaboration among individuals in NSF education programs. Utilized diverse statistical tools such as centrality scores, graph level indices, cluster analysis, sociograms, and exponential random graph models to quantify and compare networks.Text Mining – Automatically extracted sentiment and topics from journal articles, and identified emerging fields of science using latent Dirichlet allocation, support vector machines, and time series analysis.Statistical Modeling – Applied general linear models, outlier detection, hypothesis testing, sensitivity analysis, and visualization techniques to large datasets in order to complete research objectives.Survey Analysis – Developed questionnaires, collected responses, and reported statistics. Created a new inter-rater reliability coefficient to handle missing data and published findings in a proceedings journal.