Serve as the leading expert in data science methods within CDC's National Center of Injury Prevention and Control.Consult and collaborate with internal and external partners to leverage data science methods to solve complex problems and improve public health research.

Acted as science officer for one of the five funded Youth Violence Prevention Centers (YVPC).Served as the co-lead of the United States implementation of the Cardiff Model for Violence Prevention. This long-standing project requires managing contracts, addressing complex data linkage issues, providing technical assistance to localities implementing the Cardiff Violence, and collaborating with both external partners and internal CDC staff and scientists across the Injury Center.Served as a recognized expert within the Division of Violence Prevention in advance statistical and “big data” methods. These include supervised and unsupervised machine learning methods, natural language processing, and collecting and managing large datasets consisting of both structured and unstructured data. In addition, collaborate with the Office of Informatics and the Data Science Team within the Division of Injury Prevention when project scope requires addition computational resources or personnel.

Lead project manager, data analyst, and statistical adviser for CDC’s Division of Violence Prevention’ REDUCE (Real time Ensemble Data to Understand Suicide Epidemiology) project, a collaboration between CDC and Georgia Tech to develop novel informatics-based methods to provide real-time surveillance for severe behavioral outcomes and improve public health intervention programs targeting suicide and self-directed violence.Developed and lead a research agenda consisting of multiple intramural behavioral research projects focused on using novel real-time data sources to enhance surveillance of suicide, self-directed violence, and related upstream factors.

Designed, conducted, and managed projects using novel data sources (e.g., social media and syndromic surveillance data), epidemiological methods, and statistical/informatics techniques to address the need for real-time surveillance of multiple severely negative behavioral outcomes such as depression, self-directed violence, and suicide.Lead data analyst and statistical adviser for the Cardiff Violence Prevention Model (Cardiff Model) in the United States. A project that promotes data sharing between a local hospital emergency department and police department to identify violence-related injury hot spots through geographic mapping which helps police, hospital and community partners to better allocate resources for violence prevention.

Project manager and data analyst on project entitled “The utility of historic crime, demographic, and business data in prospectively predicting violent crime at the geographic level of a block group.”- Provide technical support and expertise for initial coding and management of a large dataset using the R statistical programming language- Assist with data analysis by researching relevant R statistical packages and testing different predictive modeling methods including logistic regression and random forests- Develop and implement code to access and utilize the Google Maps API and the American Community Survey API

Data management expert on a project to improve the Georgia Maternal and Child Health Repository- Designed and created a user guide for the Georgia Maternal and Child Health Data Repository to be distributed to partner agencies- Cleaned, evaluated, and summarized the Georgia Maternal and Child Health Data Repository SQL database using Microsoft SQL Management Server 2008 and SAS 9.4

Input survey data that seeks to study the stress, sleeping habits, eating habits, and exercise habitsof undergraduates at Emory University- Entered data consisting of over 1,000 ‘Health 100’ Student Surveys using Adobe Forms Central- Coordinated orally and in writing with fellow research assistants to ensure that surveys were divided and- Communicated with primary investigators about issues with survey questions (e.g. commonly skipped questions)

Provided supplementary instruction to students in Pre-Algebra and Elementary Algebra courses during designated laboratory hours and tutored students in various mathematics and science courses in the College’s Academic Resource Center Supervised five student assistant tutors